{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/scene-generation/papers/ran/1","list_of":"/task/scene-generation","task":"Scene Generation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"ran","order_definition":"only papers where Syntology ran at least one harvested sample; date (newest first), ties by arXiv id","caption":"We ran code from the paper's repository; we did not run it on this task or check it against the task's benchmarks.","absence":"A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.","page":1,"pages_in_order":1,"rows_per_page":100,"rows":[1,47],"of":47,"counts":{"archive_papers_tagged":309,"with_a_code_link":122,"where_syntology_ran_a_sample":47,"not_listed_spam_title":0,"listed":309,"listed_where_code_ran":47,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":43,"every_run_a_failure_of_syntologys_instrument":4,"listed_with_a_run_with_no_instrument_failure":43,"listed_every_run_a_failure_of_syntologys_instrument":4,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/scene-generation/papers/ran/1","prev":null,"next":null,"papers":[{"url":"/paper/xverse-consistent-multi-subject-control-of","slug":"xverse-consistent-multi-subject-control-of","title":"XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation","date":"2025-06-26","arxiv_id":"2506.21416","repositories_listed":1,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/xverse-consistent-multi-subject-control-of#ran","syntology_url":"https://syntology.ai/paper/2506.21416","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2506.21416"}},"official":{"repos":["bytedance/xverse"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/long-term-traffic-simulation-with-interleaved","slug":"long-term-traffic-simulation-with-interleaved","title":"Long-term Traffic Simulation with Interleaved Autoregressive Motion and Scenario Generation","date":"2025-06-20","arxiv_id":"2506.17213","repositories_listed":1,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/long-term-traffic-simulation-with-interleaved#ran","syntology_url":"https://syntology.ai/paper/2506.17213","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2506.17213"}},"official":{"repos":["orangesodahub/infgen"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/holotime-taming-video-diffusion-models-for","slug":"holotime-taming-video-diffusion-models-for","title":"HoloTime: Taming Video Diffusion Models for Panoramic 4D Scene Generation","date":"2025-04-30","arxiv_id":"2504.21650","repositories_listed":1,"syntology":{"n":8,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":1,"n_no_contract":3,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 1 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/holotime-taming-video-diffusion-models-for#ran","syntology_url":"https://syntology.ai/paper/2504.21650","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2504.21650"}},"official":{"repos":["pku-yuangroup/holotime"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/metaspatial-reinforcing-3d-spatial-reasoning","slug":"metaspatial-reinforcing-3d-spatial-reasoning","title":"MetaSpatial: Reinforcing 3D Spatial Reasoning in VLMs for the Metaverse","date":"2025-03-24","arxiv_id":"2503.18470","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/metaspatial-reinforcing-3d-spatial-reasoning#ran","syntology_url":"https://syntology.ai/paper/2503.18470","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.18470"}},"official":{"repos":["pzyseere/metaspatial"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/global-local-tree-search-for-language-guided","slug":"global-local-tree-search-for-language-guided","title":"Global-Local Tree Search in VLMs for 3D Indoor Scene Generation","date":"2025-03-24","arxiv_id":"2503.18476","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/global-local-tree-search-for-language-guided#ran","syntology_url":"https://syntology.ai/paper/2503.18476","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.18476"}},"official":{"repos":["dw-dengwei/treesearchgen"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/mmgdreamer-mixed-modality-graph-for-geometry-1","slug":"mmgdreamer-mixed-modality-graph-for-geometry-1","title":"MMGDreamer: Mixed-Modality Graph for Geometry-Controllable 3D Indoor Scene Generation","date":"2025-02-09","arxiv_id":"2502.05874","repositories_listed":1,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/mmgdreamer-mixed-modality-graph-for-geometry-1#ran","syntology_url":"https://syntology.ai/paper/2502.05874","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.05874"}},"official":{"repos":["yangzhifeio/MMGDreamer"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/hermes-a-unified-self-driving-world-model-for","slug":"hermes-a-unified-self-driving-world-model-for","title":"HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and Generation","date":"2025-01-24","arxiv_id":"2501.14729","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/hermes-a-unified-self-driving-world-model-for#ran","syntology_url":"https://syntology.ai/paper/2501.14729","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2501.14729"}},"official":{"repos":["lmd0311/hermes"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/laion-sg-an-enhanced-large-scale-dataset-for","slug":"laion-sg-an-enhanced-large-scale-dataset-for","title":"LAION-SG: An Enhanced Large-Scale Dataset for Training Complex Image-Text Models with Structural Annotations","date":"2024-12-11","arxiv_id":"2412.08580","repositories_listed":2,"syntology":{"n":23,"n_ran":12,"n_constructed":0,"n_ran_checked":10,"n_instrument":2,"n_unverified":11,"n_honours":0,"n_violates":2,"n_no_contract":8,"n_pointer_only":13,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 2 violated, 8 with no contract checked; 2 where Syntology's instrument failed) · 11 unverified","sample_list":"/paper/laion-sg-an-enhanced-large-scale-dataset-for#ran","syntology_url":"https://syntology.ai/paper/2412.08580","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.08580"}},"official":{"repos":["mengcye/LAION-SG"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":6,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/uniscene-unified-occupancy-centric-driving","slug":"uniscene-unified-occupancy-centric-driving","title":"UniScene: Unified Occupancy-centric Driving Scene Generation","date":"2024-12-06","arxiv_id":"2412.05435","repositories_listed":1,"syntology":{"n":11,"n_ran":9,"n_constructed":0,"n_ran_checked":8,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/uniscene-unified-occupancy-centric-driving#ran","syntology_url":"https://syntology.ai/paper/2412.05435","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.05435"}},"official":null}},{"url":"/paper/scenegenagent-precise-industrial-scene","slug":"scenegenagent-precise-industrial-scene","title":"SceneGenAgent: Precise Industrial Scene Generation with Coding Agent","date":"2024-10-29","arxiv_id":"2410.21909","repositories_listed":1,"syntology":{"n":11,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/scenegenagent-precise-industrial-scene#ran","syntology_url":"https://syntology.ai/paper/2410.21909","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.21909"}},"official":{"repos":["thudm/scenegenagent"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/scenecraft-layout-guided-3d-scene-generation","slug":"scenecraft-layout-guided-3d-scene-generation","title":"SceneCraft: Layout-Guided 3D Scene Generation","date":"2024-10-11","arxiv_id":"2410.09049","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/scenecraft-layout-guided-3d-scene-generation#ran","syntology_url":"https://syntology.ai/paper/2410.09049","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.09049"}},"official":{"repos":["orangesodahub/scenecraft"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/riskawarebench-towards-evaluating-physical","slug":"riskawarebench-towards-evaluating-physical","title":"EARBench: Towards Evaluating Physical Risk Awareness for Task Planning of Foundation Model-based Embodied AI Agents","date":"2024-08-08","arxiv_id":"2408.04449","repositories_listed":2,"syntology":{"n":11,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/riskawarebench-towards-evaluating-physical#ran","syntology_url":"https://syntology.ai/paper/2408.04449","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2408.04449"}},"official":{"repos":["zihao-ai/eairiskbench","zihao-ai/earbench"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/solving-motion-planning-tasks-with-a-scalable","slug":"solving-motion-planning-tasks-with-a-scalable","title":"Solving Motion Planning Tasks with a Scalable Generative Model","date":"2024-07-03","arxiv_id":"2407.02797","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/solving-motion-planning-tasks-with-a-scalable#ran","syntology_url":"https://syntology.ai/paper/2407.02797","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2407.02797"}},"official":{"repos":["horizonrobotics/gump"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/director3d-real-world-camera-trajectory-and","slug":"director3d-real-world-camera-trajectory-and","title":"Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text","date":"2024-06-25","arxiv_id":"2406.17601","repositories_listed":1,"syntology":{"n":15,"n_ran":12,"n_constructed":0,"n_ran_checked":7,"n_instrument":5,"n_unverified":3,"n_honours":3,"n_violates":0,"n_no_contract":4,"n_pointer_only":15,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 3 honoured, 0 violated, 4 with no contract checked; 5 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/director3d-real-world-camera-trajectory-and#ran","syntology_url":"https://syntology.ai/paper/2406.17601","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.17601"}},"official":{"repos":["imlixinyang/director3d"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/gaussiancity-generative-gaussian-splatting","slug":"gaussiancity-generative-gaussian-splatting","title":"GaussianCity: Generative Gaussian Splatting for Unbounded 3D City Generation","date":"2024-06-10","arxiv_id":"2406.06526","repositories_listed":1,"syntology":{"n":10,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":10,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/gaussiancity-generative-gaussian-splatting#ran","syntology_url":"https://syntology.ai/paper/2406.06526","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2406.06526"}},"official":{"repos":["hzxie/GaussianCity"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/reparo-compositional-3d-assets-generation","slug":"reparo-compositional-3d-assets-generation","title":"REPARO: Compositional 3D Assets Generation with Differentiable 3D Layout Alignment","date":"2024-05-28","arxiv_id":"2405.18525","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/reparo-compositional-3d-assets-generation#ran","syntology_url":"https://syntology.ai/paper/2405.18525","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.18525"}},"official":{"repos":["VincentHancoder/REPARO"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/dreamscene4d-dynamic-multi-object-scene","slug":"dreamscene4d-dynamic-multi-object-scene","title":"DreamScene4D: Dynamic Multi-Object Scene Generation from Monocular Videos","date":"2024-05-03","arxiv_id":"2405.02280","repositories_listed":1,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/dreamscene4d-dynamic-multi-object-scene#ran","syntology_url":"https://syntology.ai/paper/2405.02280","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.02280"}},"official":{"repos":["dreamscene4d/dreamscene4d"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/wcdt-world-centric-diffusion-transformer-for","slug":"wcdt-world-centric-diffusion-transformer-for","title":"WcDT: World-centric Diffusion Transformer for Traffic Scene Generation","date":"2024-04-02","arxiv_id":"2404.02082","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/wcdt-world-centric-diffusion-transformer-for#ran","syntology_url":"https://syntology.ai/paper/2404.02082","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.02082"}},"official":{"repos":["yangchen1997/wcdt"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-realistic-scene-generation-with-lidar","slug":"towards-realistic-scene-generation-with-lidar","title":"Towards Realistic Scene Generation with LiDAR Diffusion Models","date":"2024-03-31","arxiv_id":"2404.00815","repositories_listed":1,"syntology":{"n":8,"n_ran":5,"n_constructed":4,"n_ran_checked":5,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 4 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/towards-realistic-scene-generation-with-lidar#ran","syntology_url":"https://syntology.ai/paper/2404.00815","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.00815"}},"official":{"repos":["hancyran/lidar-diffusion"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":4,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/semcity-semantic-scene-generation-with","slug":"semcity-semantic-scene-generation-with","title":"SemCity: Semantic Scene Generation with Triplane Diffusion","date":"2024-03-12","arxiv_id":"2403.07773","repositories_listed":1,"syntology":{"n":22,"n_ran":18,"n_constructed":0,"n_ran_checked":15,"n_instrument":3,"n_unverified":4,"n_honours":3,"n_violates":0,"n_no_contract":12,"n_pointer_only":10,"phrase":"18 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 3 honoured, 0 violated, 12 with no contract checked; 3 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/semcity-semantic-scene-generation-with#ran","syntology_url":"https://syntology.ai/paper/2403.07773","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.07773"}},"official":{"repos":["zoomin-lee/semcity"],"state":"official (archive's flag): 18 ran","n_ran":18,"n_constructed":0,"n_ran_no_instrument_failure":15,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/blockfusion-expandable-3d-scene-generation","slug":"blockfusion-expandable-3d-scene-generation","title":"BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane Extrapolation","date":"2024-01-30","arxiv_id":"2401.17053","repositories_listed":1,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":1,"n_no_contract":5,"n_pointer_only":9,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 1 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/blockfusion-expandable-3d-scene-generation#ran","syntology_url":"https://syntology.ai/paper/2401.17053","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.17053"}},"official":{"repos":["Tencent/BlockFusion"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/xcube-mathcal-x-3-large-scale-3d-generative","slug":"xcube-mathcal-x-3-large-scale-3d-generative","title":"XCube: Large-Scale 3D Generative Modeling using Sparse Voxel Hierarchies","date":"2023-12-06","arxiv_id":"2312.03806","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":5,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/xcube-mathcal-x-3-large-scale-3d-generative#ran","syntology_url":"https://syntology.ai/paper/2312.03806","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.03806"}},"official":{"repos":["nv-tlabs/XCube"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/wovogen-world-volume-aware-diffusion-for","slug":"wovogen-world-volume-aware-diffusion-for","title":"WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation","date":"2023-12-05","arxiv_id":"2312.02934","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/wovogen-world-volume-aware-diffusion-for#ran","syntology_url":"https://syntology.ai/paper/2312.02934","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2312.02934"}},"official":{"repos":["fudan-zvg/wovogen"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/pyramid-diffusion-for-fine-3d-large-scene","slug":"pyramid-diffusion-for-fine-3d-large-scene","title":"Pyramid Diffusion for Fine 3D Large Scene Generation","date":"2023-11-20","arxiv_id":"2311.12085","repositories_listed":2,"syntology":{"n":12,"n_ran":11,"n_constructed":0,"n_ran_checked":5,"n_instrument":6,"n_unverified":1,"n_honours":3,"n_violates":1,"n_no_contract":1,"n_pointer_only":4,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 3 honoured, 1 violated, 1 with no contract checked; 6 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/pyramid-diffusion-for-fine-3d-large-scene#ran","syntology_url":"https://syntology.ai/paper/2311.12085","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.12085"}},"official":{"repos":["yuhengliu02/pyramid-discrete-diffusion","Yuheng-SWJTU/pyramid-discrete-diffusion"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/high-fidelity-person-centric-subject-to-image","slug":"high-fidelity-person-centric-subject-to-image","title":"High-fidelity Person-centric Subject-to-Image Synthesis","date":"2023-11-17","arxiv_id":"2311.10329","repositories_listed":1,"syntology":{"n":11,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":6,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/high-fidelity-person-centric-subject-to-image#ran","syntology_url":"https://syntology.ai/paper/2311.10329","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.10329"}},"official":{"repos":["codegoat24/face-diffuser"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/llm-blueprint-enabling-text-to-image","slug":"llm-blueprint-enabling-text-to-image","title":"LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts","date":"2023-10-16","arxiv_id":"2310.10640","repositories_listed":1,"syntology":{"n":12,"n_ran":10,"n_constructed":0,"n_ran_checked":9,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":12,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/llm-blueprint-enabling-text-to-image#ran","syntology_url":"https://syntology.ai/paper/2310.10640","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.10640"}},"official":{"repos":["hananshafi/llmblueprint"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/citydreamer-compositional-generative-model-of","slug":"citydreamer-compositional-generative-model-of","title":"CityDreamer: Compositional Generative Model of Unbounded 3D Cities","date":"2023-09-01","arxiv_id":"2309.00610","repositories_listed":1,"syntology":{"n":9,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":9,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/citydreamer-compositional-generative-model-of#ran","syntology_url":"https://syntology.ai/paper/2309.00610","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.00610"}},"official":{"repos":["hzxie/CityDreamer"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/language-conditioned-traffic-generation","slug":"language-conditioned-traffic-generation","title":"Language Conditioned Traffic Generation","date":"2023-07-16","arxiv_id":"2307.07947","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/language-conditioned-traffic-generation#ran","syntology_url":"https://syntology.ai/paper/2307.07947","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.07947"}},"official":{"repos":["Ariostgx/lctgen"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/commonscenes-generating-commonsense-3d-indoor","slug":"commonscenes-generating-commonsense-3d-indoor","title":"CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graph Diffusion","date":"2023-05-25","arxiv_id":"2305.16283","repositories_listed":1,"syntology":{"n":25,"n_ran":11,"n_constructed":6,"n_ran_checked":9,"n_instrument":2,"n_unverified":14,"n_honours":1,"n_violates":0,"n_no_contract":8,"n_pointer_only":25,"phrase":"11 ran (of which 6 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 0 violated, 8 with no contract checked; 2 where Syntology's instrument failed) · 14 unverified","sample_list":"/paper/commonscenes-generating-commonsense-3d-indoor#ran","syntology_url":"https://syntology.ai/paper/2305.16283","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.16283"}},"official":{"repos":["ymxlzgy/commonscenes"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":6,"n_ran_no_instrument_failure":9,"n_unverified":14,"ran_from_kinds":["official"]}}},{"url":"/paper/text2nerf-text-driven-3d-scene-generation","slug":"text2nerf-text-driven-3d-scene-generation","title":"Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fields","date":"2023-05-19","arxiv_id":"2305.11588","repositories_listed":1,"syntology":{"n":17,"n_ran":13,"n_constructed":0,"n_ran_checked":11,"n_instrument":2,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":5,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 2 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/text2nerf-text-driven-3d-scene-generation#ran","syntology_url":"https://syntology.ai/paper/2305.11588","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.11588"}},"official":{"repos":["eckertzhang/text2nerf"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/neuralfield-ldm-scene-generation-with","slug":"neuralfield-ldm-scene-generation-with","title":"NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Models","date":"2023-04-19","arxiv_id":"2304.09787","repositories_listed":0,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":5,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":3,"n_no_contract":2,"n_pointer_only":3,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 3 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/neuralfield-ldm-scene-generation-with#ran","syntology_url":"https://syntology.ai/paper/2304.09787","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2304.09787"}},"official":null}},{"url":"/paper/meshdiffusion-score-based-generative-3d-mesh","slug":"meshdiffusion-score-based-generative-3d-mesh","title":"MeshDiffusion: Score-based Generative 3D Mesh Modeling","date":"2023-03-14","arxiv_id":"2303.08133","repositories_listed":1,"syntology":{"n":14,"n_ran":10,"n_constructed":0,"n_ran_checked":6,"n_instrument":4,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":4,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 4 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/meshdiffusion-score-based-generative-3d-mesh#ran","syntology_url":"https://syntology.ai/paper/2303.08133","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.08133"}},"official":{"repos":["lzzcd001/MeshDiffusion"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["community","official","unlocated"]}}},{"url":"/paper/neural-block-slot-representations","slug":"neural-block-slot-representations","title":"Neural Systematic Binder","date":"2022-11-02","arxiv_id":"2211.01177","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/neural-block-slot-representations#ran","syntology_url":"https://syntology.ai/paper/2211.01177","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.01177"}},"official":null}},{"url":"/paper/slot-order-matters-for-compositional-scene","slug":"slot-order-matters-for-compositional-scene","title":"Towards Improving the Generation Quality of Autoregressive Slot VAEs","date":"2022-06-03","arxiv_id":"2206.01370","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/slot-order-matters-for-compositional-scene#ran","syntology_url":"https://syntology.ai/paper/2206.01370","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.01370"}},"official":{"repos":["pemami4911/segregate-relate-imagine"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/modeling-image-composition-for-complex-scene","slug":"modeling-image-composition-for-complex-scene","title":"Modeling Image Composition for Complex Scene Generation","date":"2022-06-02","arxiv_id":"2206.00923","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/modeling-image-composition-for-complex-scene#ran","syntology_url":"https://syntology.ai/paper/2206.00923","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.00923"}},"official":{"repos":["johndreamer/twfa"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/compositional-transformers-for-scene","slug":"compositional-transformers-for-scene","title":"Compositional Transformers for Scene Generation","date":"2021-11-17","arxiv_id":"2111.08960","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/compositional-transformers-for-scene#ran","syntology_url":"https://syntology.ai/paper/2111.08960","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.08960"}},"official":{"repos":["dorarad/gansformer"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/infinitygan-towards-infinite-resolution-image","slug":"infinitygan-towards-infinite-resolution-image","title":"InfinityGAN: Towards Infinite-Pixel Image Synthesis","date":"2021-04-08","arxiv_id":"2104.03963","repositories_listed":1,"syntology":{"n":14,"n_ran":7,"n_constructed":2,"n_ran_checked":3,"n_instrument":4,"n_unverified":7,"n_honours":1,"n_violates":0,"n_no_contract":2,"n_pointer_only":14,"phrase":"7 ran (of which 2 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 4 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/infinitygan-towards-infinite-resolution-image#ran","syntology_url":"https://syntology.ai/paper/2104.03963","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.03963"}},"official":{"repos":["hubert0527/infinityGAN"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":2,"n_ran_no_instrument_failure":3,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/retrievalfuse-neural-3d-scene-reconstruction","slug":"retrievalfuse-neural-3d-scene-reconstruction","title":"RetrievalFuse: Neural 3D Scene Reconstruction with a Database","date":"2021-03-31","arxiv_id":"2104.00024","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":3,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":3,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","sample_list":"/paper/retrievalfuse-neural-3d-scene-reconstruction#ran","syntology_url":"https://syntology.ai/paper/2104.00024","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.00024"}},"official":{"repos":["nihalsid/retrieval-fuse"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/generative-adversarial-transformers","slug":"generative-adversarial-transformers","title":"Generative Adversarial Transformers","date":"2021-03-01","arxiv_id":"2103.01209","repositories_listed":2,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/generative-adversarial-transformers#ran","syntology_url":"https://syntology.ai/paper/2103.01209","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.01209"}},"official":{"repos":["dorarad/gansformer"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/pi-gan-periodic-implicit-generative","slug":"pi-gan-periodic-implicit-generative","title":"pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis","date":"2020-12-02","arxiv_id":"2012.00926","repositories_listed":3,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":1,"n_no_contract":0,"n_pointer_only":2,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/pi-gan-periodic-implicit-generative#ran","syntology_url":"https://syntology.ai/paper/2012.00926","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2012.00926"}},"official":{"repos":["marcoamonteiro/pi-GAN"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["listed","unlocated"]}}},{"url":"/paper/end-to-end-optimization-of-scene-layout-1","slug":"end-to-end-optimization-of-scene-layout-1","title":"End-to-End Optimization of Scene Layout","date":"2020-07-23","arxiv_id":"2007.11744","repositories_listed":1,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/end-to-end-optimization-of-scene-layout-1#ran","syntology_url":"https://syntology.ai/paper/2007.11744","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.11744"}},"official":{"repos":["aluo-x/3D_SLN"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/graf-generative-radiance-fields-for-3d-aware","slug":"graf-generative-radiance-fields-for-3d-aware","title":"GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis","date":"2020-07-05","arxiv_id":"2007.02442","repositories_listed":1,"syntology":{"n":12,"n_ran":10,"n_constructed":0,"n_ran_checked":9,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":1,"n_no_contract":8,"n_pointer_only":1,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 1 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/graf-generative-radiance-fields-for-3d-aware#ran","syntology_url":"https://syntology.ai/paper/2007.02442","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.02442"}},"official":{"repos":["autonomousvision/graf"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-canonical-representations-for-scene","slug":"learning-canonical-representations-for-scene","title":"Learning Canonical Representations for Scene Graph to Image Generation","date":"2019-12-16","arxiv_id":"1912.07414","repositories_listed":2,"syntology":{"n":17,"n_ran":10,"n_constructed":0,"n_ran_checked":8,"n_instrument":2,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 2 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/learning-canonical-representations-for-scene#ran","syntology_url":"https://syntology.ai/paper/1912.07414","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.07414"}},"official":{"repos":["roeiherz/CanonicalSg2Im"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/specifying-object-attributes-and-relations-in","slug":"specifying-object-attributes-and-relations-in","title":"Specifying Object Attributes and Relations in Interactive Scene Generation","date":"2019-09-11","arxiv_id":"1909.05379","repositories_listed":2,"syntology":{"n":16,"n_ran":15,"n_constructed":0,"n_ran_checked":15,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":15,"n_pointer_only":3,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/specifying-object-attributes-and-relations-in#ran","syntology_url":"https://syntology.ai/paper/1909.05379","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.05379"}},"official":{"repos":["ashual/scene_generation"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":0,"n_ran_no_instrument_failure":15,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/scenegraphnet-neural-message-passing-for-3d","slug":"scenegraphnet-neural-message-passing-for-3d","title":"SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentation","date":"2019-07-25","arxiv_id":"1907.11308","repositories_listed":2,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/scenegraphnet-neural-message-passing-for-3d#ran","syntology_url":"https://syntology.ai/paper/1907.11308","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1907.11308"}},"official":{"repos":["yzhou359/3DIndoor-SceneGraphNet"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/layoutvae-stochastic-scene-layout-generation","slug":"layoutvae-stochastic-scene-layout-generation","title":"LayoutVAE: Stochastic Scene Layout Generation From a Label Set","date":"2019-07-24","arxiv_id":"1907.10719","repositories_listed":2,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/layoutvae-stochastic-scene-layout-generation#ran","syntology_url":"https://syntology.ai/paper/1907.10719","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1907.10719"}},"official":null}},{"url":"/paper/layoutgan-generating-graphic-layouts-with","slug":"layoutgan-generating-graphic-layouts-with","title":"LayoutGAN: Generating Graphic Layouts with Wireframe Discriminators","date":"2019-01-21","arxiv_id":"1901.06767","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/layoutgan-generating-graphic-layouts-with#ran","syntology_url":"https://syntology.ai/paper/1901.06767","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1901.06767"}},"official":null}}],"record_sha256":"172ed45c08dd41208ee8c045d6789b3f3fbef36b3e8d335a3fee19f372c39a4e","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}