{"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/pose-estimation/papers/5","list_of":"/task/pose-estimation","task":"Pose Estimation","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":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":5,"pages_in_order":43,"rows_per_page":100,"rows":[401,500],"of":4228,"counts":{"archive_papers_tagged":4228,"with_a_code_link":1679,"where_syntology_ran_a_sample":376,"not_listed_spam_title":0,"listed":4228,"listed_where_code_ran":376,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":327,"every_run_a_failure_of_syntologys_instrument":49,"listed_with_a_run_with_no_instrument_failure":327,"listed_every_run_a_failure_of_syntologys_instrument":49,"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/pose-estimation","prev":"/task/pose-estimation/papers/4","next":"/task/pose-estimation/papers/6","papers":[{"url":"/paper/seglocnet-multimodal-localization-network-for","slug":"seglocnet-multimodal-localization-network-for","title":"SegLocNet: Multimodal Localization Network for Autonomous Driving via Bird's-Eye-View Segmentation","date":"2025-02-27","arxiv_id":"2502.20077","repositories_listed":1,"syntology":null},{"url":"/paper/learning-structure-supporting-dependencies","slug":"learning-structure-supporting-dependencies","title":"Learning Structure-Supporting Dependencies via Keypoint Interactive Transformer for General Mammal Pose Estimation","date":"2025-02-25","arxiv_id":"2502.18214","repositories_listed":1,"syntology":null},{"url":"/paper/depropose-deficiency-proof-3d-human-pose","slug":"depropose-deficiency-proof-3d-human-pose","title":"DeProPose: Deficiency-Proof 3D Human Pose Estimation via Adaptive Multi-View Fusion","date":"2025-02-23","arxiv_id":"2502.16419","repositories_listed":1,"syntology":null},{"url":"/paper/simhand-mining-similar-hands-for-large-scale","slug":"simhand-mining-similar-hands-for-large-scale","title":"SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training","date":"2025-02-21","arxiv_id":"2502.15251","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":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/simhand-mining-similar-hands-for-large-scale#ran","syntology_url":"https://syntology.ai/paper/2502.15251","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.15251"}},"official":{"repos":["ut-vision/simhand"],"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/codiff-conditional-diffusion-model-for","slug":"codiff-conditional-diffusion-model-for","title":"CoDiff: Conditional Diffusion Model for Collaborative 3D Object Detection","date":"2025-02-17","arxiv_id":"2502.14891","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/codiff-conditional-diffusion-model-for#ran","syntology_url":"https://syntology.ai/paper/2502.14891","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.14891"}},"official":{"repos":["huangzhe885/codiff"],"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","unlocated"]}}},{"url":"/paper/varges-improving-variation-in-co-speech-3d","slug":"varges-improving-variation-in-co-speech-3d","title":"VarGes: Improving Variation in Co-Speech 3D Gesture Generation via StyleCLIPS","date":"2025-02-15","arxiv_id":"2502.10729","repositories_listed":1,"syntology":null},{"url":"/paper/manual2skill-learning-to-read-manuals-and","slug":"manual2skill-learning-to-read-manuals-and","title":"Manual2Skill: Learning to Read Manuals and Acquire Robotic Skills for Furniture Assembly Using Vision-Language Models","date":"2025-02-14","arxiv_id":"2502.10090","repositories_listed":1,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"9 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; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/manual2skill-learning-to-read-manuals-and#ran","syntology_url":"https://syntology.ai/paper/2502.10090","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.10090"}},"official":{"repos":["owensun2004/Manual2Skill"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/lir-livo-a-lightweight-robust-lidar-vision","slug":"lir-livo-a-lightweight-robust-lidar-vision","title":"LIR-LIVO: A Lightweight,Robust LiDAR/Vision/Inertial Odometry with Illumination-Resilient Deep Features","date":"2025-02-12","arxiv_id":"2502.08676","repositories_listed":1,"syntology":null},{"url":"/paper/measuring-physical-plausibility-of-3d-human","slug":"measuring-physical-plausibility-of-3d-human","title":"Measuring Physical Plausibility of 3D Human Poses Using Physics Simulation","date":"2025-02-06","arxiv_id":"2502.04483","repositories_listed":1,"syntology":null},{"url":"/paper/diff9d-diffusion-based-domain-generalized","slug":"diff9d-diffusion-based-domain-generalized","title":"Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation","date":"2025-02-04","arxiv_id":"2502.02525","repositories_listed":1,"syntology":null},{"url":"/paper/xrf-v2-a-dataset-for-action-summarization","slug":"xrf-v2-a-dataset-for-action-summarization","title":"XRF V2: A Dataset for Action Summarization with Wi-Fi Signals, and IMUs in Phones, Watches, Earbuds, and Glasses","date":"2025-01-31","arxiv_id":"2501.19034","repositories_listed":1,"syntology":null},{"url":"/paper/simpledepthpose-fast-and-reliable-human-pose","slug":"simpledepthpose-fast-and-reliable-human-pose","title":"SimpleDepthPose: Fast and Reliable Human Pose Estimation with RGBD-Images","date":"2025-01-30","arxiv_id":"2501.18478","repositories_listed":1,"syntology":null},{"url":"/paper/3d-2d-registration-of-angiograms-using","slug":"3d-2d-registration-of-angiograms-using","title":"3D/2D Registration of Angiograms using Silhouette-based Differentiable Rendering","date":"2025-01-24","arxiv_id":"2501.14918","repositories_listed":1,"syntology":null},{"url":"/paper/egohand-ego-centric-hand-pose-estimation-and","slug":"egohand-ego-centric-hand-pose-estimation-and","title":"EgoHand: Ego-centric Hand Pose Estimation and Gesture Recognition with Head-mounted Millimeter-wave Radar and IMUs","date":"2025-01-23","arxiv_id":"2501.13805","repositories_listed":1,"syntology":null},{"url":"/paper/fast3r-towards-3d-reconstruction-of-1000","slug":"fast3r-towards-3d-reconstruction-of-1000","title":"Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass","date":"2025-01-23","arxiv_id":"2501.13928","repositories_listed":1,"syntology":null},{"url":"/paper/gs-cpr-efficient-camera-pose-refinement-via","slug":"gs-cpr-efficient-camera-pose-refinement-via","title":"GS-CPR: Efficient Camera Pose Refinement via 3D Gaussian Splatting","date":"2025-01-23","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/landmarker-a-toolkit-for-anatomical-landmark","slug":"landmarker-a-toolkit-for-anatomical-landmark","title":"landmarker: a Toolkit for Anatomical Landmark Localization in 2D/3D Images","date":"2025-01-17","arxiv_id":"2501.10098","repositories_listed":1,"syntology":null},{"url":"/paper/towards-robust-and-realistic-human-pose","slug":"towards-robust-and-realistic-human-pose","title":"Towards Robust and Realistic Human Pose Estimation via WiFi Signals","date":"2025-01-16","arxiv_id":"2501.09411","repositories_listed":1,"syntology":null},{"url":"/paper/bright-vo-brightness-guided-hybrid","slug":"bright-vo-brightness-guided-hybrid","title":"BRIGHT-VO: Brightness-Guided Hybrid Transformer for Visual Odometry with Multi-modality Refinement Module","date":"2025-01-15","arxiv_id":"2501.08659","repositories_listed":1,"syntology":null},{"url":"/paper/poseidon-a-vit-based-architecture-for-multi","slug":"poseidon-a-vit-based-architecture-for-multi","title":"Poseidon: A ViT-based Architecture for Multi-Frame Pose Estimation with Adaptive Frame Weighting and Multi-Scale Feature Fusion","date":"2025-01-14","arxiv_id":"2501.08446","repositories_listed":1,"syntology":null},{"url":"/paper/fixing-the-scale-and-shift-in-monocular-depth","slug":"fixing-the-scale-and-shift-in-monocular-depth","title":"RePoseD: Efficient Relative Pose Estimation With Known Depth Information","date":"2025-01-13","arxiv_id":"2501.07742","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"0 ran · 1 unverified","sample_list":"/paper/fixing-the-scale-and-shift-in-monocular-depth#ran","syntology_url":"https://syntology.ai/paper/2501.07742","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2501.07742"}},"official":{"repos":["yaqding/pose_monodepth"],"state":"official: not harvested","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":[]}}},{"url":"/paper/ekalibr-dynamic-intrinsic-calibration-for","slug":"ekalibr-dynamic-intrinsic-calibration-for","title":"eKalibr: Dynamic Intrinsic Calibration for Event Cameras From First Principles of Events","date":"2025-01-10","arxiv_id":"2501.05688","repositories_listed":1,"syntology":null},{"url":"/paper/relative-pose-estimation-through-affine","slug":"relative-pose-estimation-through-affine","title":"Relative Pose Estimation through Affine Corrections of Monocular Depth Priors","date":"2025-01-09","arxiv_id":"2501.05446","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 1 unverified","sample_list":"/paper/relative-pose-estimation-through-affine#ran","syntology_url":"https://syntology.ai/paper/2501.05446","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2501.05446"}},"official":{"repos":["markyu98/madpose"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/rolo-slam-rotation-optimized-lidar-only-slam","slug":"rolo-slam-rotation-optimized-lidar-only-slam","title":"ROLO-SLAM: Rotation-Optimized LiDAR-Only SLAM in Uneven Terrain with Ground Vehicle","date":"2025-01-04","arxiv_id":"2501.02166","repositories_listed":1,"syntology":null},{"url":"/paper/tcpformer-learning-temporal-correlation-with","slug":"tcpformer-learning-temporal-correlation-with","title":"TCPFormer: Learning Temporal Correlation with Implicit Pose Proxy for 3D Human Pose Estimation","date":"2025-01-03","arxiv_id":"2501.01770","repositories_listed":1,"syntology":null},{"url":"/paper/learning-to-filter-outlier-edges-in-global","slug":"learning-to-filter-outlier-edges-in-global","title":"Learning to Filter Outlier Edges in Global SfM","date":"2025-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/pidloc-cross-view-pose-optimization-network","slug":"pidloc-cross-view-pose-optimization-network","title":"PIDLoc: Cross-View Pose Optimization Network Inspired by PID Controllers","date":"2025-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/exploiting-aggregation-and-segregation-of","slug":"exploiting-aggregation-and-segregation-of","title":"Exploiting Aggregation and Segregation of Representations for Domain Adaptive Human Pose Estimation","date":"2024-12-29","arxiv_id":"2412.20538","repositories_listed":1,"syntology":null},{"url":"/paper/gsplatloc-ultra-precise-camera-localization","slug":"gsplatloc-ultra-precise-camera-localization","title":"GSplatLoc: Ultra-Precise Camera Localization via 3D Gaussian Splatting","date":"2024-12-28","arxiv_id":"2412.20056","repositories_listed":1,"syntology":null},{"url":"/paper/optimizing-local-global-dependencies-for","slug":"optimizing-local-global-dependencies-for","title":"Optimizing Local-Global Dependencies for Accurate 3D Human Pose Estimation","date":"2024-12-27","arxiv_id":"2412.19676","repositories_listed":1,"syntology":null},{"url":"/paper/reconstructing-people-places-and-cameras","slug":"reconstructing-people-places-and-cameras","title":"Reconstructing People, Places, and Cameras","date":"2024-12-23","arxiv_id":"2412.17806","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":0,"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/reconstructing-people-places-and-cameras#ran","syntology_url":"https://syntology.ai/paper/2412.17806","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.17806"}},"official":{"repos":["hongsukchoi/hsfm_release"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/leveraging-consistent-spatio-temporal","slug":"leveraging-consistent-spatio-temporal","title":"Leveraging Consistent Spatio-Temporal Correspondence for Robust Visual Odometry","date":"2024-12-22","arxiv_id":"2412.16923","repositories_listed":1,"syntology":null},{"url":"/paper/pre-training-a-density-aware-pose-transformer","slug":"pre-training-a-density-aware-pose-transformer","title":"Pre-training a Density-Aware Pose Transformer for Robust LiDAR-based 3D Human Pose Estimation","date":"2024-12-18","arxiv_id":"2412.13454","repositories_listed":1,"syntology":null},{"url":"/paper/exechecker-where-did-i-go-wrong","slug":"exechecker-where-did-i-go-wrong","title":"ExeChecker: Where Did I Go Wrong?","date":"2024-12-13","arxiv_id":"2412.10573","repositories_listed":1,"syntology":null},{"url":"/paper/improve-impact-of-mobile-phones-on-remote","slug":"improve-impact-of-mobile-phones-on-remote","title":"A multimodal dataset for understanding the impact of mobile phones on remote online virtual education","date":"2024-12-13","arxiv_id":"2412.14195","repositories_listed":1,"syntology":null},{"url":"/paper/reloc3r-large-scale-training-of-relative","slug":"reloc3r-large-scale-training-of-relative","title":"Reloc3r: Large-Scale Training of Relative Camera Pose Regression for Generalizable, Fast, and Accurate Visual Localization","date":"2024-12-11","arxiv_id":"2412.08376","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"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; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/reloc3r-large-scale-training-of-relative#ran","syntology_url":"https://syntology.ai/paper/2412.08376","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.08376"}},"official":{"repos":["ffrivera0/reloc3r"],"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/an-efficient-scene-coordinate-encoding-and","slug":"an-efficient-scene-coordinate-encoding-and","title":"Enhancing Scene Coordinate Regression with Efficient Keypoint Detection and Sequential Information","date":"2024-12-09","arxiv_id":"2412.06488","repositories_listed":1,"syntology":null},{"url":"/paper/attention-enhanced-lightweight-hourglass","slug":"attention-enhanced-lightweight-hourglass","title":"Attention-Enhanced Lightweight Hourglass Network for Human Pose Estimation","date":"2024-12-09","arxiv_id":"2412.06227","repositories_listed":1,"syntology":null},{"url":"/paper/mv-dust3r-single-stage-scene-reconstruction","slug":"mv-dust3r-single-stage-scene-reconstruction","title":"MV-DUSt3R+: Single-Stage Scene Reconstruction from Sparse Views In 2 Seconds","date":"2024-12-09","arxiv_id":"2412.06974","repositories_listed":1,"syntology":null},{"url":"/paper/cascaded-multi-scale-attention-for-enhanced","slug":"cascaded-multi-scale-attention-for-enhanced","title":"Cascaded Multi-Scale Attention for Enhanced Multi-Scale Feature Extraction and Interaction with Low-Resolution Images","date":"2024-12-03","arxiv_id":"2412.02197","repositories_listed":1,"syntology":null},{"url":"/paper/probpose-a-probabilistic-approach-to-2d-human","slug":"probpose-a-probabilistic-approach-to-2d-human","title":"ProbPose: A Probabilistic Approach to 2D Human Pose Estimation","date":"2024-12-03","arxiv_id":"2412.02254","repositories_listed":1,"syntology":null},{"url":"/paper/detection-pose-estimation-and-segmentation-1","slug":"detection-pose-estimation-and-segmentation-1","title":"Detection, Pose Estimation and Segmentation for Multiple Bodies: Closing the Virtuous Circle","date":"2024-12-02","arxiv_id":"2412.01562","repositories_listed":1,"syntology":null},{"url":"/paper/emg2pose-a-large-and-diverse-benchmark-for","slug":"emg2pose-a-large-and-diverse-benchmark-for","title":"emg2pose: A Large and Diverse Benchmark for Surface Electromyographic Hand Pose Estimation","date":"2024-12-02","arxiv_id":"2412.02725","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":3,"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/emg2pose-a-large-and-diverse-benchmark-for#ran","syntology_url":"https://syntology.ai/paper/2412.02725","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2412.02725"}},"official":{"repos":["facebookresearch/emg2pose"],"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/sf-loc-a-visual-mapping-and-geo-localization","slug":"sf-loc-a-visual-mapping-and-geo-localization","title":"SF-Loc: A Visual Mapping and Geo-Localization System based on Sparse Visual Structure Frames","date":"2024-12-02","arxiv_id":"2412.01500","repositories_listed":1,"syntology":null},{"url":"/paper/particle-based-6d-object-pose-estimation-from","slug":"particle-based-6d-object-pose-estimation-from","title":"Particle-based 6D Object Pose Estimation from Point Clouds using Diffusion Models","date":"2024-12-01","arxiv_id":"2412.00835","repositories_listed":1,"syntology":null},{"url":"/paper/multiview-equivariance-improves-3d","slug":"multiview-equivariance-improves-3d","title":"Multiview Equivariance Improves 3D Correspondence Understanding with Minimal Feature Finetuning","date":"2024-11-29","arxiv_id":"2411.19458","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":2,"n_ran_checked":4,"n_instrument":1,"n_unverified":2,"n_honours":2,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"5 ran (of which 2 constructed an object rather than computing a result; 4 with no instrument failure: 2 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/multiview-equivariance-improves-3d#ran","syntology_url":"https://syntology.ai/paper/2411.19458","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.19458"}},"official":{"repos":["qq456cvb/3dcorrenhance"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":2,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/boost-3d-reconstruction-using-diffusion-based","slug":"boost-3d-reconstruction-using-diffusion-based","title":"Boost 3D Reconstruction using Diffusion-based Monocular Camera Calibration","date":"2024-11-26","arxiv_id":"2411.17240","repositories_listed":1,"syntology":null},{"url":"/paper/robopepp-vision-based-robot-pose-and-joint","slug":"robopepp-vision-based-robot-pose-and-joint","title":"RoboPEPP: Vision-Based Robot Pose and Joint Angle Estimation through Embedding Predictive Pre-Training","date":"2024-11-26","arxiv_id":"2411.17662","repositories_listed":1,"syntology":{"n":13,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":13,"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) · 6 unverified","sample_list":"/paper/robopepp-vision-based-robot-pose-and-joint#ran","syntology_url":"https://syntology.ai/paper/2411.17662","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.17662"}},"official":{"repos":["raktimgg/robopepp"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/edge-weight-prediction-for-category-agnostic","slug":"edge-weight-prediction-for-category-agnostic","title":"Edge Weight Prediction For Category-Agnostic Pose Estimation","date":"2024-11-25","arxiv_id":"2411.16665","repositories_listed":1,"syntology":null},{"url":"/paper/one-diffusion-to-generate-them-all","slug":"one-diffusion-to-generate-them-all","title":"One Diffusion to Generate Them All","date":"2024-11-25","arxiv_id":"2411.16318","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":5,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/one-diffusion-to-generate-them-all#ran","syntology_url":"https://syntology.ai/paper/2411.16318","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.16318"}},"official":{"repos":["lehduong/onediffusion"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/splatflow-multi-view-rectified-flow-model-for","slug":"splatflow-multi-view-rectified-flow-model-for","title":"SplatFlow: Multi-View Rectified Flow Model for 3D Gaussian Splatting Synthesis","date":"2024-11-25","arxiv_id":"2411.16443","repositories_listed":1,"syntology":{"n":18,"n_ran":13,"n_constructed":0,"n_ran_checked":13,"n_instrument":0,"n_unverified":5,"n_honours":1,"n_violates":0,"n_no_contract":12,"n_pointer_only":18,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 1 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/splatflow-multi-view-rectified-flow-model-for#ran","syntology_url":"https://syntology.ai/paper/2411.16443","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.16443"}},"official":{"repos":["gohyojun15/SplatFlow"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":13,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/peng-pose-enhanced-geo-localisation","slug":"peng-pose-enhanced-geo-localisation","title":"PEnG: Pose-Enhanced Geo-Localisation","date":"2024-11-24","arxiv_id":"2411.15742","repositories_listed":1,"syntology":null},{"url":"/paper/dino-x-a-unified-vision-model-for-open-world","slug":"dino-x-a-unified-vision-model-for-open-world","title":"DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding","date":"2024-11-21","arxiv_id":"2411.14347","repositories_listed":1,"syntology":null},{"url":"/paper/implicit-and-parametric-avatar-pose-and-shape","slug":"implicit-and-parametric-avatar-pose-and-shape","title":"Implicit and Parametric Avatar Pose and Shape Estimation From a Single Frontal Image of a Clothed Human","date":"2024-11-21","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/incrowd-vi-a-realistic-visual-inertial","slug":"incrowd-vi-a-realistic-visual-inertial","title":"InCrowd-VI: A Realistic Visual-Inertial Dataset for Evaluating SLAM in Indoor Pedestrian-Rich Spaces for Human Navigation","date":"2024-11-21","arxiv_id":"2411.14358","repositories_listed":1,"syntology":null},{"url":"/paper/x-as-supervision-contending-with-depth","slug":"x-as-supervision-contending-with-depth","title":"X as Supervision: Contending with Depth Ambiguity in Unsupervised Monocular 3D Pose Estimation","date":"2024-11-20","arxiv_id":"2411.13026","repositories_listed":1,"syntology":null},{"url":"/paper/viopose-violin-performance-4d-pose-estimation","slug":"viopose-violin-performance-4d-pose-estimation","title":"VioPose: Violin Performance 4D Pose Estimation by Hierarchical Audiovisual Inference","date":"2024-11-19","arxiv_id":"2411.13607","repositories_listed":1,"syntology":null},{"url":"/paper/ikea-manuals-at-work-4d-grounding-of-assembly","slug":"ikea-manuals-at-work-4d-grounding-of-assembly","title":"IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos","date":"2024-11-18","arxiv_id":"2411.11409","repositories_listed":1,"syntology":{"n":18,"n_ran":12,"n_constructed":0,"n_ran_checked":7,"n_instrument":5,"n_unverified":6,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":18,"phrase":"12 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; 5 where Syntology's instrument failed) · 6 unverified","sample_list":"/paper/ikea-manuals-at-work-4d-grounding-of-assembly#ran","syntology_url":"https://syntology.ai/paper/2411.11409","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.11409"}},"official":{"repos":["yunongLiu1/IKEA-Manuals-at-Work"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/spars3r-semantic-prior-alignment-and","slug":"spars3r-semantic-prior-alignment-and","title":"SPARS3R: Semantic Prior Alignment and Regularization for Sparse 3D Reconstruction","date":"2024-11-15","arxiv_id":"2411.12592","repositories_listed":1,"syntology":null},{"url":"/paper/usp-gaussian-unifying-spike-based-image","slug":"usp-gaussian-unifying-spike-based-image","title":"USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting","date":"2024-11-15","arxiv_id":"2411.10504","repositories_listed":1,"syntology":null},{"url":"/paper/deeparuco-improved-detection-of-square","slug":"deeparuco-improved-detection-of-square","title":"DeepArUco++: Improved detection of square fiducial markers in challenging lighting conditions","date":"2024-11-08","arxiv_id":"2411.05552","repositories_listed":1,"syntology":null},{"url":"/paper/social-egomesh-estimation","slug":"social-egomesh-estimation","title":"Social EgoMesh Estimation","date":"2024-11-07","arxiv_id":"2411.04598","repositories_listed":1,"syntology":null},{"url":"/paper/activating-self-attention-for-multi-scene","slug":"activating-self-attention-for-multi-scene","title":"Activating Self-Attention for Multi-Scene Absolute Pose Regression","date":"2024-11-03","arxiv_id":"2411.01443","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 1 unverified","sample_list":"/paper/activating-self-attention-for-multi-scene#ran","syntology_url":"https://syntology.ai/paper/2411.01443","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2411.01443"}},"official":{"repos":["dlalth557/ActMST"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/no-pose-no-problem-surprisingly-simple-3d","slug":"no-pose-no-problem-surprisingly-simple-3d","title":"No Pose, No Problem: Surprisingly Simple 3D Gaussian Splats from Sparse Unposed Images","date":"2024-10-31","arxiv_id":"2410.24207","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 1 unverified","sample_list":"/paper/no-pose-no-problem-surprisingly-simple-3d#ran","syntology_url":"https://syntology.ai/paper/2410.24207","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.24207"}},"official":{"repos":["cvg/NoPoSplat"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/scrream-scan-register-render-and-map-a","slug":"scrream-scan-register-render-and-map-a","title":"SCRREAM : SCan, Register, REnder And Map:A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark","date":"2024-10-30","arxiv_id":"2410.22715","repositories_listed":1,"syntology":null},{"url":"/paper/ei-nexus-towards-unmediated-and-flexible","slug":"ei-nexus-towards-unmediated-and-flexible","title":"EI-Nexus: Towards Unmediated and Flexible Inter-Modality Local Feature Extraction and Matching for Event-Image Data","date":"2024-10-29","arxiv_id":"2410.21743","repositories_listed":1,"syntology":null},{"url":"/paper/blapose-enhancing-3d-human-pose-estimation","slug":"blapose-enhancing-3d-human-pose-estimation","title":"BLAPose: Enhancing 3D Human Pose Estimation with Bone Length Adjustment","date":"2024-10-28","arxiv_id":"2410.20731","repositories_listed":1,"syntology":null},{"url":"/paper/neural-fields-in-robotics-a-survey","slug":"neural-fields-in-robotics-a-survey","title":"Neural Fields in Robotics: A Survey","date":"2024-10-26","arxiv_id":"2410.20220","repositories_listed":1,"syntology":null},{"url":"/paper/voxelkeypointfusion-generalizable-multi-view","slug":"voxelkeypointfusion-generalizable-multi-view","title":"VoxelKeypointFusion: Generalizable Multi-View Multi-Person Pose Estimation","date":"2024-10-24","arxiv_id":"2410.18723","repositories_listed":1,"syntology":null},{"url":"/paper/robust-two-view-geometry-estimation-with","slug":"robust-two-view-geometry-estimation-with","title":"Robust Two-View Geometry Estimation with Implicit Differentiation","date":"2024-10-23","arxiv_id":"2410.17983","repositories_listed":1,"syntology":null},{"url":"/paper/yolov11-an-overview-of-the-key-architectural","slug":"yolov11-an-overview-of-the-key-architectural","title":"YOLOv11: An Overview of the Key Architectural Enhancements","date":"2024-10-23","arxiv_id":"2410.17725","repositories_listed":1,"syntology":null},{"url":"/paper/pose-pose-estimation-of-virtual-sync-exhibit","slug":"pose-pose-estimation-of-virtual-sync-exhibit","title":"POSE: Pose estimation Of virtual Sync Exhibit system","date":"2024-10-20","arxiv_id":"2410.15343","repositories_listed":1,"syntology":null},{"url":"/paper/towards-multi-modal-animal-pose-estimation-an","slug":"towards-multi-modal-animal-pose-estimation-an","title":"Towards Multi-Modal Animal Pose Estimation: A Survey and In-Depth Analysis","date":"2024-10-12","arxiv_id":"2410.09312","repositories_listed":1,"syntology":null},{"url":"/paper/look-gauss-no-pose-novel-view-synthesis-using","slug":"look-gauss-no-pose-novel-view-synthesis-using","title":"Look Gauss, No Pose: Novel View Synthesis using Gaussian Splatting without Accurate Pose Initialization","date":"2024-10-11","arxiv_id":"2410.08743","repositories_listed":1,"syntology":null},{"url":"/paper/optimal-state-dynamics-estimation-for-physics","slug":"optimal-state-dynamics-estimation-for-physics","title":"Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videos","date":"2024-10-10","arxiv_id":"2410.07795","repositories_listed":1,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":2,"n_honours":0,"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; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/optimal-state-dynamics-estimation-for-physics#ran","syntology_url":"https://syntology.ai/paper/2410.07795","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.07795"}},"official":{"repos":["cuongle1206/osdcap"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/spectrack-learned-multi-rotation-tracking-via","slug":"spectrack-learned-multi-rotation-tracking-via","title":"SpecTrack: Learned Multi-Rotation Tracking via Speckle Imaging","date":"2024-10-08","arxiv_id":"2410.06028","repositories_listed":1,"syntology":null},{"url":"/paper/enhancing-3d-human-pose-estimation-amidst","slug":"enhancing-3d-human-pose-estimation-amidst","title":"Enhancing 3D Human Pose Estimation Amidst Severe Occlusion with Dual Transformer Fusion","date":"2024-10-06","arxiv_id":"2410.04574","repositories_listed":1,"syntology":null},{"url":"/paper/litevloc-map-lite-visual-localization-for","slug":"litevloc-map-lite-visual-localization-for","title":"LiteVLoc: Map-Lite Visual Localization for Image Goal Navigation","date":"2024-10-06","arxiv_id":"2410.04419","repositories_listed":1,"syntology":null},{"url":"/paper/test-time-adaptation-for-keypoint-based","slug":"test-time-adaptation-for-keypoint-based","title":"Test-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on Predicted-View Synthesis","date":"2024-10-05","arxiv_id":"2410.04298","repositories_listed":1,"syntology":null},{"url":"/paper/monst3r-a-simple-approach-for-estimating","slug":"monst3r-a-simple-approach-for-estimating","title":"MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion","date":"2024-10-04","arxiv_id":"2410.03825","repositories_listed":1,"syntology":null},{"url":"/paper/why-sample-space-matters-keyframe-sampling","slug":"why-sample-space-matters-keyframe-sampling","title":"Why Sample Space Matters: Keyframe Sampling Optimization for LiDAR-based Place Recognition","date":"2024-10-03","arxiv_id":"2410.02643","repositories_listed":1,"syntology":null},{"url":"/paper/rad-a-dataset-and-benchmark-for-real-life","slug":"rad-a-dataset-and-benchmark-for-real-life","title":"RAD: A Dataset and Benchmark for Real-Life Anomaly Detection with Robotic Observations","date":"2024-10-01","arxiv_id":"2410.00713","repositories_listed":1,"syntology":null},{"url":"/paper/puzzleboard-a-new-camera-calibration-pattern","slug":"puzzleboard-a-new-camera-calibration-pattern","title":"PuzzleBoard: A New Camera Calibration Pattern with Position Encoding","date":"2024-09-30","arxiv_id":"2409.20127","repositories_listed":1,"syntology":null},{"url":"/paper/pplns-parametric-piecewise-linear-networks","slug":"pplns-parametric-piecewise-linear-networks","title":"PPLNs: Parametric Piecewise Linear Networks for Event-Based Temporal Modeling and Beyond","date":"2024-09-29","arxiv_id":"2409.19772","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":1,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":6,"phrase":"6 ran (of which 1 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) · 0 unverified","sample_list":"/paper/pplns-parametric-piecewise-linear-networks#ran","syntology_url":"https://syntology.ai/paper/2409.19772","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2409.19772"}},"official":{"repos":["chensong1995/ppln"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":1,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/leveraging-anthropometric-measurements-to","slug":"leveraging-anthropometric-measurements-to","title":"Leveraging Anthropometric Measurements to Improve Human Mesh Estimation and Ensure Consistent Body Shapes","date":"2024-09-26","arxiv_id":"2409.17671","repositories_listed":1,"syntology":null},{"url":"/paper/omni6d-large-vocabulary-3d-object-dataset-for","slug":"omni6d-large-vocabulary-3d-object-dataset-for","title":"Omni6D: Large-Vocabulary 3D Object Dataset for Category-Level 6D Object Pose Estimation","date":"2024-09-26","arxiv_id":"2409.18261","repositories_listed":1,"syntology":null},{"url":"/paper/lapose-laplacian-mixture-shape-modeling-for","slug":"lapose-laplacian-mixture-shape-modeling-for","title":"LaPose: Laplacian Mixture Shape Modeling for RGB-Based Category-Level Object Pose Estimation","date":"2024-09-24","arxiv_id":"2409.15727","repositories_listed":1,"syntology":{"n":12,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":1,"n_no_contract":9,"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, 1 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/lapose-laplacian-mixture-shape-modeling-for#ran","syntology_url":"https://syntology.ai/paper/2409.15727","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2409.15727"}},"official":{"repos":["lolrudy/lapose"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/branchposenet-characterizing-tree-branching","slug":"branchposenet-characterizing-tree-branching","title":"BranchPoseNet: Characterizing tree branching with a deep learning-based pose estimation approach","date":"2024-09-23","arxiv_id":"2409.14755","repositories_listed":1,"syntology":null},{"url":"/paper/wilor-end-to-end-3d-hand-localization-and","slug":"wilor-end-to-end-3d-hand-localization-and","title":"WiLoR: End-to-end 3D Hand Localization and Reconstruction in-the-wild","date":"2024-09-18","arxiv_id":"2409.12259","repositories_listed":1,"syntology":null},{"url":"/paper/omnigen-unified-image-generation","slug":"omnigen-unified-image-generation","title":"OmniGen: Unified Image Generation","date":"2024-09-17","arxiv_id":"2409.11340","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":5,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"8 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; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/omnigen-unified-image-generation#ran","syntology_url":"https://syntology.ai/paper/2409.11340","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2409.11340"}},"official":{"repos":["vectorspacelab/omnigen"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/hifi-cs-towards-open-vocabulary-visual","slug":"hifi-cs-towards-open-vocabulary-visual","title":"HiFi-CS: Towards Open Vocabulary Visual Grounding For Robotic Grasping Using Vision-Language Models","date":"2024-09-16","arxiv_id":"2409.10419","repositories_listed":1,"syntology":null},{"url":"/paper/causal-transformer-for-fusion-and-pose","slug":"causal-transformer-for-fusion-and-pose","title":"Causal Transformer for Fusion and Pose Estimation in Deep Visual Inertial Odometry","date":"2024-09-13","arxiv_id":"2409.08769","repositories_listed":1,"syntology":null},{"url":"/paper/wheelposer-sparse-imu-based-body-pose","slug":"wheelposer-sparse-imu-based-body-pose","title":"WheelPoser: Sparse-IMU Based Body Pose Estimation for Wheelchair Users","date":"2024-09-13","arxiv_id":"2409.08494","repositories_listed":1,"syntology":null},{"url":"/paper/bayesian-inverse-graphics-for-few-shot","slug":"bayesian-inverse-graphics-for-few-shot","title":"Bayesian Inverse Graphics for Few-Shot Concept Learning","date":"2024-09-12","arxiv_id":"2409.08351","repositories_listed":1,"syntology":null},{"url":"/paper/deep-learning-and-machine-learning-techniques","slug":"deep-learning-and-machine-learning-techniques","title":"Deep learning and machine learning techniques for head pose estimation: a survey","date":"2024-09-12","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/gst-precise-3d-human-body-from-a-single-image","slug":"gst-precise-3d-human-body-from-a-single-image","title":"GST: Precise 3D Human Body from a Single Image with Gaussian Splatting Transformers","date":"2024-09-06","arxiv_id":"2409.04196","repositories_listed":1,"syntology":null},{"url":"/paper/head-pose-estimation-based-on-5d-rotation","slug":"head-pose-estimation-based-on-5d-rotation","title":"Head Pose Estimation Based on 5D Rotation Representation","date":"2024-09-03","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/spike-3d-human-pose-from-point-cloud","slug":"spike-3d-human-pose-from-point-cloud","title":"SPiKE: 3D Human Pose from Point Cloud Sequences","date":"2024-09-03","arxiv_id":"2409.01879","repositories_listed":1,"syntology":null},{"url":"/paper/grpose-learning-graph-relations-for-human","slug":"grpose-learning-graph-relations-for-human","title":"GRPose: Learning Graph Relations for Human Image Generation with Pose Priors","date":"2024-08-29","arxiv_id":"2408.16540","repositories_listed":1,"syntology":null},{"url":"/paper/op-align-object-level-and-part-level","slug":"op-align-object-level-and-part-level","title":"OP-Align: Object-level and Part-level Alignment for Self-supervised Category-level Articulated Object Pose Estimation","date":"2024-08-29","arxiv_id":"2408.16547","repositories_listed":1,"syntology":null}],"record_sha256":"de7931d103fc6004224935ed7b344a1b3b5f79e2e399bd3f77eda52ff96a83fa","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}