{"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/autonomous-driving/papers/12","list_of":"/task/autonomous-driving","task":"Autonomous Driving","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":12,"pages_in_order":61,"rows_per_page":100,"rows":[1101,1200],"of":6092,"counts":{"archive_papers_tagged":6092,"with_a_code_link":2091,"where_syntology_ran_a_sample":470,"not_listed_spam_title":0,"listed":6092,"listed_where_code_ran":470,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":415,"every_run_a_failure_of_syntologys_instrument":55,"listed_with_a_run_with_no_instrument_failure":415,"listed_every_run_a_failure_of_syntologys_instrument":55,"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/autonomous-driving","prev":"/task/autonomous-driving/papers/11","next":"/task/autonomous-driving/papers/13","papers":[{"url":"/paper/you-only-look-at-once-for-real-time-and","slug":"you-only-look-at-once-for-real-time-and","title":"You Only Look at Once for Real-time and Generic Multi-Task","date":"2023-10-02","arxiv_id":"2310.01641","repositories_listed":1,"syntology":null},{"url":"/paper/gaia-1-a-generative-world-model-for","slug":"gaia-1-a-generative-world-model-for","title":"GAIA-1: A Generative World Model for Autonomous Driving","date":"2023-09-29","arxiv_id":"2309.17080","repositories_listed":1,"syntology":null},{"url":"/paper/autonomous-driving-using-spiking-neural","slug":"autonomous-driving-using-spiking-neural","title":"Autonomous Driving using Spiking Neural Networks on Dynamic Vision Sensor Data: A Case Study of Traffic Light Change Detection","date":"2023-09-27","arxiv_id":"2311.09225","repositories_listed":1,"syntology":null},{"url":"/paper/infraparis-a-multi-modal-and-multi-task","slug":"infraparis-a-multi-modal-and-multi-task","title":"InfraParis: A multi-modal and multi-task autonomous driving dataset","date":"2023-09-27","arxiv_id":"2309.15751","repositories_listed":1,"syntology":null},{"url":"/paper/clrmatchnet-enhancing-curved-lane-detection","slug":"clrmatchnet-enhancing-curved-lane-detection","title":"CLRmatchNet: Enhancing Curved Lane Detection with Deep Matching Process","date":"2023-09-26","arxiv_id":"2309.15204","repositories_listed":1,"syntology":null},{"url":"/paper/distillbev-boosting-multi-camera-3d-object","slug":"distillbev-boosting-multi-camera-3d-object","title":"DistillBEV: Boosting Multi-Camera 3D Object Detection with Cross-Modal Knowledge Distillation","date":"2023-09-26","arxiv_id":"2309.15109","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/distillbev-boosting-multi-camera-3d-object#ran","syntology_url":"https://syntology.ai/paper/2309.15109","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.15109"}},"official":{"repos":["qcraftai/distill-bev"],"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/benchmarking-local-robustness-of-high","slug":"benchmarking-local-robustness-of-high","title":"Benchmarking Local Robustness of High-Accuracy Binary Neural Networks for Enhanced Traffic Sign Recognition","date":"2023-09-25","arxiv_id":"2310.03033","repositories_listed":1,"syntology":null},{"url":"/paper/continual-driving-policy-optimization-with","slug":"continual-driving-policy-optimization-with","title":"Continual Driving Policy Optimization with Closed-Loop Individualized Curricula","date":"2023-09-25","arxiv_id":"2309.14209","repositories_listed":1,"syntology":null},{"url":"/paper/stackelberg-driver-model-for-continual-policy","slug":"stackelberg-driver-model-for-continual-policy","title":"Stackelberg Driver Model for Continual Policy Improvement in Scenario-Based Closed-Loop Autonomous Driving","date":"2023-09-25","arxiv_id":"2309.14235","repositories_listed":1,"syntology":null},{"url":"/paper/distribution-aware-continual-test-time","slug":"distribution-aware-continual-test-time","title":"Distribution-Aware Continual Test-Time Adaptation for Semantic Segmentation","date":"2023-09-24","arxiv_id":"2309.13604","repositories_listed":1,"syntology":null},{"url":"/paper/feddrive-v2-an-analysis-of-the-impact-of","slug":"feddrive-v2-an-analysis-of-the-impact-of","title":"FedDrive v2: an Analysis of the Impact of Label Skewness in Federated Semantic Segmentation for Autonomous Driving","date":"2023-09-23","arxiv_id":"2309.13336","repositories_listed":1,"syntology":null},{"url":"/paper/pixel-wise-smoothing-for-certified-robustness","slug":"pixel-wise-smoothing-for-certified-robustness","title":"Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations","date":"2023-09-22","arxiv_id":"2309.13150","repositories_listed":1,"syntology":null},{"url":"/paper/sequential-action-induced-invariant","slug":"sequential-action-induced-invariant","title":"Sequential Action-Induced Invariant Representation for Reinforcement Learning","date":"2023-09-22","arxiv_id":"2309.12628","repositories_listed":1,"syntology":null},{"url":"/paper/distributional-pareto-optimal-multi-objective","slug":"distributional-pareto-optimal-multi-objective","title":"Distributional Pareto-Optimal Multi-Objective Reinforcement Learning","date":"2023-09-21","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/fgfusion-fine-grained-lidar-camera-fusion-for","slug":"fgfusion-fine-grained-lidar-camera-fusion-for","title":"FGFusion: Fine-Grained Lidar-Camera Fusion for 3D Object Detection","date":"2023-09-21","arxiv_id":"2309.11804","repositories_listed":1,"syntology":null},{"url":"/paper/monouni-a-unified-vehicle-and-infrastructure","slug":"monouni-a-unified-vehicle-and-infrastructure","title":"MonoUNI: A Unified Vehicle and Infrastructure-side Monocular 3D Object Detection Network with Sufficient Depth Clues","date":"2023-09-21","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/panovos-bridging-non-panoramic-and-panoramic","slug":"panovos-bridging-non-panoramic-and-panoramic","title":"PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentation","date":"2023-09-21","arxiv_id":"2309.12303","repositories_listed":1,"syntology":null},{"url":"/paper/rethinking-imitation-based-planner-for","slug":"rethinking-imitation-based-planner-for","title":"Rethinking Imitation-based Planner for Autonomous Driving","date":"2023-09-19","arxiv_id":"2309.10443","repositories_listed":1,"syntology":null},{"url":"/paper/spot-scalable-3d-pre-training-via-occupancy","slug":"spot-scalable-3d-pre-training-via-occupancy","title":"SPOT: Scalable 3D Pre-training via Occupancy Prediction for Learning Transferable 3D Representations","date":"2023-09-19","arxiv_id":"2309.10527","repositories_listed":1,"syntology":null},{"url":"/paper/ar-tta-a-simple-method-for-real-world","slug":"ar-tta-a-simple-method-for-real-world","title":"AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation","date":"2023-09-18","arxiv_id":"2309.10109","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/ar-tta-a-simple-method-for-real-world#ran","syntology_url":"https://syntology.ai/paper/2309.10109","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.10109"}},"official":{"repos":["dmn-sjk/ar-tta"],"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/drivedreamer-towards-real-world-driven-world","slug":"drivedreamer-towards-real-world-driven-world","title":"DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving","date":"2023-09-18","arxiv_id":"2309.09777","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/drivedreamer-towards-real-world-driven-world#ran","syntology_url":"https://syntology.ai/paper/2309.09777","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.09777"}},"official":null}},{"url":"/paper/pre-training-on-synthetic-driving-data-for","slug":"pre-training-on-synthetic-driving-data-for","title":"Pre-training on Synthetic Driving Data for Trajectory Prediction","date":"2023-09-18","arxiv_id":"2309.10121","repositories_listed":1,"syntology":null},{"url":"/paper/renderocc-vision-centric-3d-occupancy","slug":"renderocc-vision-centric-3d-occupancy","title":"RenderOcc: Vision-Centric 3D Occupancy Prediction with 2D Rendering Supervision","date":"2023-09-18","arxiv_id":"2309.09502","repositories_listed":1,"syntology":null},{"url":"/paper/deep-neighbor-layer-aggregation-for","slug":"deep-neighbor-layer-aggregation-for","title":"Deep Neighbor Layer Aggregation for Lightweight Self-Supervised Monocular Depth Estimation","date":"2023-09-17","arxiv_id":"2309.09272","repositories_listed":1,"syntology":null},{"url":"/paper/rmp-a-random-mask-pretrain-framework-for","slug":"rmp-a-random-mask-pretrain-framework-for","title":"RMP: A Random Mask Pretrain Framework for Motion Prediction","date":"2023-09-16","arxiv_id":"2309.08989","repositories_listed":1,"syntology":null},{"url":"/paper/mtd-multi-timestep-detector-for-delayed","slug":"mtd-multi-timestep-detector-for-delayed","title":"MTD: Multi-Timestep Detector for Delayed Streaming Perception","date":"2023-09-13","arxiv_id":"2309.06742","repositories_listed":1,"syntology":null},{"url":"/paper/the-moral-machine-experiment-on-large","slug":"the-moral-machine-experiment-on-large","title":"The Moral Machine Experiment on Large Language Models","date":"2023-09-12","arxiv_id":"2309.05958","repositories_listed":1,"syntology":null},{"url":"/paper/which-framework-is-suitable-for-online-3d","slug":"which-framework-is-suitable-for-online-3d","title":"Which Framework is Suitable for Online 3D Multi-Object Tracking for Autonomous Driving with Automotive 4D Imaging Radar?","date":"2023-09-12","arxiv_id":"2309.06036","repositories_listed":1,"syntology":null},{"url":"/paper/language-prompt-for-autonomous-driving","slug":"language-prompt-for-autonomous-driving","title":"Language Prompt for Autonomous Driving","date":"2023-09-08","arxiv_id":"2309.04379","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":1,"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/language-prompt-for-autonomous-driving#ran","syntology_url":"https://syntology.ai/paper/2309.04379","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.04379"}},"official":{"repos":["wudongming97/prompt4driving"],"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/context-aware-3d-object-localization-from","slug":"context-aware-3d-object-localization-from","title":"Context-Aware 3D Object Localization from Single Calibrated Images: A Study of Basketballs","date":"2023-09-07","arxiv_id":"2309.03640","repositories_listed":1,"syntology":null},{"url":"/paper/fisheyepp4av-a-privacy-preserving-method-for","slug":"fisheyepp4av-a-privacy-preserving-method-for","title":"FisheyePP4AV: A privacy-preserving method for autonomous vehicles on fisheye camera images","date":"2023-09-07","arxiv_id":"2309.03799","repositories_listed":1,"syntology":null},{"url":"/paper/interactionnet-joint-planning-and-prediction","slug":"interactionnet-joint-planning-and-prediction","title":"InteractionNet: Joint Planning and Prediction for Autonomous Driving with Transformers","date":"2023-09-07","arxiv_id":"2309.03475","repositories_listed":1,"syntology":null},{"url":"/paper/efficient-baselines-for-motion-prediction-in","slug":"efficient-baselines-for-motion-prediction-in","title":"Efficient Baselines for Motion Prediction in Autonomous Driving","date":"2023-09-06","arxiv_id":"2309.03387","repositories_listed":1,"syntology":null},{"url":"/paper/enhancing-6-dof-object-pose-estimation","slug":"enhancing-6-dof-object-pose-estimation","title":"Enhancing 6-DoF Object Pose Estimation through Multiple Modality Fusion: A Hybrid CNN Architecture with Cross-Layer and Cross-Modal Integration","date":"2023-09-06","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/bevtrack-a-simple-baseline-for-3d-single","slug":"bevtrack-a-simple-baseline-for-3d-single","title":"BEVTrack: A Simple and Strong Baseline for 3D Single Object Tracking in Bird's-Eye View","date":"2023-09-05","arxiv_id":"2309.02185","repositories_listed":1,"syntology":null},{"url":"/paper/snow-removal-for-lidar-point-clouds-with","slug":"snow-removal-for-lidar-point-clouds-with","title":"Snow Removal for LiDAR Point Clouds with Spatio-temporal Conditional Random Fields","date":"2023-09-04","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/tsttc-a-large-scale-dataset-for-time-to","slug":"tsttc-a-large-scale-dataset-for-time-to","title":"TSTTC: A Large-Scale Dataset for Time-to-Contact Estimation in Driving Scenarios","date":"2023-09-04","arxiv_id":"2309.01539","repositories_listed":1,"syntology":null},{"url":"/paper/sqldepth-generalizable-self-supervised-fine","slug":"sqldepth-generalizable-self-supervised-fine","title":"SQLdepth: Generalizable Self-Supervised Fine-Structured Monocular Depth Estimation","date":"2023-09-01","arxiv_id":"2309.00526","repositories_listed":1,"syntology":null},{"url":"/paper/btseg-barlow-twins-regularization-for-domain","slug":"btseg-barlow-twins-regularization-for-domain","title":"BTSeg: Barlow Twins Regularization for Domain Adaptation in Semantic Segmentation","date":"2023-08-31","arxiv_id":"2308.16819","repositories_listed":1,"syntology":null},{"url":"/paper/pointocc-cylindrical-tri-perspective-view-for","slug":"pointocc-cylindrical-tri-perspective-view-for","title":"PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Prediction","date":"2023-08-31","arxiv_id":"2308.16896","repositories_listed":1,"syntology":null},{"url":"/paper/drl-based-trajectory-tracking-for-motion","slug":"drl-based-trajectory-tracking-for-motion","title":"DRL-Based Trajectory Tracking for Motion-Related Modules in Autonomous Driving","date":"2023-08-30","arxiv_id":"2308.15991","repositories_listed":1,"syntology":{"n":8,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":0,"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) · 0 unverified","sample_list":"/paper/drl-based-trajectory-tracking-for-motion#ran","syntology_url":"https://syntology.ai/paper/2308.15991","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.15991"}},"official":{"repos":["marmotatzju/drl-based-trajectory-tracking"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/complementing-onboard-sensors-with-satellite","slug":"complementing-onboard-sensors-with-satellite","title":"Complementing Onboard Sensors with Satellite Map: A New Perspective for HD Map Construction","date":"2023-08-29","arxiv_id":"2308.15427","repositories_listed":1,"syntology":null},{"url":"/paper/1st-place-solution-for-the-5th-lsvos","slug":"1st-place-solution-for-the-5th-lsvos","title":"1st Place Solution for the 5th LSVOS Challenge: Video Instance Segmentation","date":"2023-08-28","arxiv_id":"2308.14392","repositories_listed":1,"syntology":null},{"url":"/paper/fixating-on-attention-integrating-human-eye","slug":"fixating-on-attention-integrating-human-eye","title":"Gaze-Informed Vision Transformers: Predicting Driving Decisions Under Uncertainty","date":"2023-08-26","arxiv_id":"2308.13969","repositories_listed":1,"syntology":null},{"url":"/paper/sogdet-semantic-occupancy-guided-multi-view","slug":"sogdet-semantic-occupancy-guided-multi-view","title":"SOGDet: Semantic-Occupancy Guided Multi-view 3D Object Detection","date":"2023-08-26","arxiv_id":"2308.13794","repositories_listed":1,"syntology":null},{"url":"/paper/stride-street-view-based-environmental","slug":"stride-street-view-based-environmental","title":"STRIDE: Street View-based Environmental Feature Detection and Pedestrian Collision Prediction","date":"2023-08-25","arxiv_id":"2308.13183","repositories_listed":1,"syntology":null},{"url":"/paper/perspective-aware-convolution-for-monocular","slug":"perspective-aware-convolution-for-monocular","title":"Perspective-aware Convolution for Monocular 3D Object Detection","date":"2023-08-24","arxiv_id":"2308.12938","repositories_listed":1,"syntology":null},{"url":"/paper/streammapnet-streaming-mapping-network-for","slug":"streammapnet-streaming-mapping-network-for","title":"StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Construction","date":"2023-08-24","arxiv_id":"2308.12570","repositories_listed":1,"syntology":null},{"url":"/paper/unim-2-ae-multi-modal-masked-autoencoders","slug":"unim-2-ae-multi-modal-masked-autoencoders","title":"UniM$^2$AE: Multi-modal Masked Autoencoders with Unified 3D Representation for 3D Perception in Autonomous Driving","date":"2023-08-21","arxiv_id":"2308.10421","repositories_listed":1,"syntology":null},{"url":"/paper/quantile-based-maximum-likelihood-training","slug":"quantile-based-maximum-likelihood-training","title":"Quantile-based Maximum Likelihood Training for Outlier Detection","date":"2023-08-20","arxiv_id":"2310.06085","repositories_listed":1,"syntology":null},{"url":"/paper/datasetequity-are-all-samples-created-equal","slug":"datasetequity-are-all-samples-created-equal","title":"DatasetEquity: Are All Samples Created Equal? In The Quest For Equity Within Datasets","date":"2023-08-19","arxiv_id":"2308.09878","repositories_listed":1,"syntology":null},{"url":"/paper/focusflow-boosting-key-points-optical-flow","slug":"focusflow-boosting-key-points-optical-flow","title":"FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving","date":"2023-08-14","arxiv_id":"2308.07104","repositories_listed":1,"syntology":null},{"url":"/paper/focalformer3d-focusing-on-hard-instance-for","slug":"focalformer3d-focusing-on-hard-instance-for","title":"FocalFormer3D : Focusing on Hard Instance for 3D Object Detection","date":"2023-08-08","arxiv_id":"2308.04556","repositories_listed":1,"syntology":null},{"url":"/paper/latr-3d-lane-detection-from-monocular-images","slug":"latr-3d-lane-detection-from-monocular-images","title":"LATR: 3D Lane Detection from Monocular Images with Transformer","date":"2023-08-08","arxiv_id":"2308.04583","repositories_listed":1,"syntology":{"n":14,"n_ran":11,"n_constructed":0,"n_ran_checked":10,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":2,"phrase":"11 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/latr-3d-lane-detection-from-monocular-images#ran","syntology_url":"https://syntology.ai/paper/2308.04583","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.04583"}},"official":{"repos":["jmoonr/latr"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/smarla-a-safety-monitoring-approach-for-deep","slug":"smarla-a-safety-monitoring-approach-for-deep","title":"SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning Agents","date":"2023-08-03","arxiv_id":"2308.02594","repositories_listed":1,"syntology":null},{"url":"/paper/ugains-uncertainty-guided-anomaly-instance","slug":"ugains-uncertainty-guided-anomaly-instance","title":"UGainS: Uncertainty Guided Anomaly Instance Segmentation","date":"2023-08-03","arxiv_id":"2308.02046","repositories_listed":1,"syntology":null},{"url":"/paper/fusionad-multi-modality-fusion-for-prediction","slug":"fusionad-multi-modality-fusion-for-prediction","title":"FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving","date":"2023-08-02","arxiv_id":"2308.01006","repositories_listed":1,"syntology":null},{"url":"/paper/driveadapter-breaking-the-coupling-barrier-of","slug":"driveadapter-breaking-the-coupling-barrier-of","title":"DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving","date":"2023-08-01","arxiv_id":"2308.00398","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"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) · 1 unverified","sample_list":"/paper/driveadapter-breaking-the-coupling-barrier-of#ran","syntology_url":"https://syntology.ai/paper/2308.00398","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.00398"}},"official":{"repos":["opendrivelab/driveadapter"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/echoes-beyond-points-unleashing-the-power-of","slug":"echoes-beyond-points-unleashing-the-power-of","title":"Echoes Beyond Points: Unleashing the Power of Raw Radar Data in Multi-modality Fusion","date":"2023-07-31","arxiv_id":"2307.16532","repositories_listed":1,"syntology":null},{"url":"/paper/benchmarking-anomaly-detection-system-on","slug":"benchmarking-anomaly-detection-system-on","title":"Benchmarking Jetson Edge Devices with an End-to-end Video-based Anomaly Detection System","date":"2023-07-28","arxiv_id":"2307.16834","repositories_listed":1,"syntology":null},{"url":"/paper/mars-an-instance-aware-modular-and-realistic","slug":"mars-an-instance-aware-modular-and-realistic","title":"MARS: An Instance-aware, Modular and Realistic Simulator for Autonomous Driving","date":"2023-07-27","arxiv_id":"2307.15058","repositories_listed":1,"syntology":null},{"url":"/paper/car-studio-learning-car-radiance-fields-from","slug":"car-studio-learning-car-radiance-fields-from","title":"Car-Studio: Learning Car Radiance Fields from Single-View and Endless In-the-wild Images","date":"2023-07-26","arxiv_id":"2307.14009","repositories_listed":1,"syntology":null},{"url":"/paper/coco-o-a-benchmark-for-object-detectors-under-1","slug":"coco-o-a-benchmark-for-object-detectors-under-1","title":"COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts","date":"2023-07-24","arxiv_id":"2307.12730","repositories_listed":1,"syntology":null},{"url":"/paper/a-simple-and-model-free-path-filtering","slug":"a-simple-and-model-free-path-filtering","title":"A Simple and Model-Free Path Filtering Algorithm for Smoothing and Accuracy","date":"2023-07-23","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/fdct-fast-depth-completion-for-transparent","slug":"fdct-fast-depth-completion-for-transparent","title":"FDCT: Fast Depth Completion for Transparent Objects","date":"2023-07-23","arxiv_id":"2307.12274","repositories_listed":1,"syntology":null},{"url":"/paper/patch-wise-point-cloud-generation-a-divide","slug":"patch-wise-point-cloud-generation-a-divide","title":"Patch-Wise Point Cloud Generation: A Divide-and-Conquer Approach","date":"2023-07-22","arxiv_id":"2307.12049","repositories_listed":1,"syntology":null},{"url":"/paper/hvdetfusion-a-simple-and-robust-camera-radar","slug":"hvdetfusion-a-simple-and-robust-camera-radar","title":"HVDetFusion: A Simple and Robust Camera-Radar Fusion Framework","date":"2023-07-21","arxiv_id":"2307.11323","repositories_listed":1,"syntology":null},{"url":"/paper/boundary-state-generation-for-testing-and","slug":"boundary-state-generation-for-testing-and","title":"Boundary State Generation for Testing and Improvement of Autonomous Driving Systems","date":"2023-07-20","arxiv_id":"2307.10590","repositories_listed":1,"syntology":null},{"url":"/paper/twinlitenet-an-efficient-and-lightweight","slug":"twinlitenet-an-efficient-and-lightweight","title":"TwinLiteNet: An Efficient and Lightweight Model for Driveable Area and Lane Segmentation in Self-Driving Cars","date":"2023-07-20","arxiv_id":"2307.10705","repositories_listed":1,"syntology":null},{"url":"/paper/backdoor-attack-against-object-detection-with","slug":"backdoor-attack-against-object-detection-with","title":"Attacking by Aligning: Clean-Label Backdoor Attacks on Object Detection","date":"2023-07-19","arxiv_id":"2307.10487","repositories_listed":1,"syntology":null},{"url":"/paper/explaining-autonomous-driving-actions-with","slug":"explaining-autonomous-driving-actions-with","title":"Explaining Autonomous Driving Actions with Visual Question Answering","date":"2023-07-19","arxiv_id":"2307.10408","repositories_listed":1,"syntology":null},{"url":"/paper/domain-adaptation-for-enhanced-object","slug":"domain-adaptation-for-enhanced-object","title":"Domain Adaptation based Object Detection for Autonomous Driving in Foggy and Rainy Weather","date":"2023-07-18","arxiv_id":"2307.09676","repositories_listed":1,"syntology":{"n":13,"n_ran":13,"n_constructed":0,"n_ran_checked":12,"n_instrument":1,"n_unverified":0,"n_honours":2,"n_violates":1,"n_no_contract":9,"n_pointer_only":0,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 2 honoured, 1 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/domain-adaptation-for-enhanced-object#ran","syntology_url":"https://syntology.ai/paper/2307.09676","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.09676"}},"official":{"repos":["jinlong17/da-detect"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-a-performance-analysis-on-pre-trained","slug":"towards-a-performance-analysis-on-pre-trained","title":"Towards a performance analysis on pre-trained Visual Question Answering models for autonomous driving","date":"2023-07-18","arxiv_id":"2307.09329","repositories_listed":1,"syntology":null},{"url":"/paper/on-the-fly-neural-style-smoothing-for-risk","slug":"on-the-fly-neural-style-smoothing-for-risk","title":"On the Fly Neural Style Smoothing for Risk-Averse Domain Generalization","date":"2023-07-17","arxiv_id":"2307.08551","repositories_listed":1,"syntology":null},{"url":"/paper/rofusion-efficient-object-detection-using","slug":"rofusion-efficient-object-detection-using","title":"ROFusion: Efficient Object Detection using Hybrid Point-wise Radar-Optical Fusion","date":"2023-07-17","arxiv_id":"2307.08233","repositories_listed":1,"syntology":null},{"url":"/paper/drive-like-a-human-rethinking-autonomous","slug":"drive-like-a-human-rethinking-autonomous","title":"Drive Like a Human: Rethinking Autonomous Driving with Large Language Models","date":"2023-07-14","arxiv_id":"2307.07162","repositories_listed":1,"syntology":null},{"url":"/paper/heal-swin-a-vision-transformer-on-the-sphere","slug":"heal-swin-a-vision-transformer-on-the-sphere","title":"HEAL-SWIN: A Vision Transformer On The Sphere","date":"2023-07-14","arxiv_id":"2307.07313","repositories_listed":1,"syntology":{"n":11,"n_ran":11,"n_constructed":0,"n_ran_checked":9,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"11 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; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/heal-swin-a-vision-transformer-on-the-sphere#ran","syntology_url":"https://syntology.ai/paper/2307.07313","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.07313"}},"official":{"repos":["janegerken/heal-swin"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/linking-vision-and-motion-for-self-supervised","slug":"linking-vision-and-motion-for-self-supervised","title":"Linking vision and motion for self-supervised object-centric perception","date":"2023-07-14","arxiv_id":"2307.07147","repositories_listed":1,"syntology":null},{"url":"/paper/deepipcv2-lidar-powered-robust-environmental","slug":"deepipcv2-lidar-powered-robust-environmental","title":"DeepIPCv2: LiDAR-powered Robust Environmental Perception and Navigational Control for Autonomous Vehicle","date":"2023-07-13","arxiv_id":"2307.06647","repositories_listed":1,"syntology":null},{"url":"/paper/limsim-a-long-term-interactive-multi-scenario","slug":"limsim-a-long-term-interactive-multi-scenario","title":"LimSim: A Long-term Interactive Multi-scenario Traffic Simulator","date":"2023-07-13","arxiv_id":"2307.06648","repositories_listed":1,"syntology":null},{"url":"/paper/large-class-separation-is-not-what-you-need","slug":"large-class-separation-is-not-what-you-need","title":"Large Class Separation is not what you need for Relational Reasoning-based OOD Detection","date":"2023-07-12","arxiv_id":"2307.06179","repositories_listed":1,"syntology":null},{"url":"/paper/one-versus-others-attention-scalable","slug":"one-versus-others-attention-scalable","title":"One-Versus-Others Attention: Scalable Multimodal Integration for Biomedical Data","date":"2023-07-11","arxiv_id":"2307.05435","repositories_listed":1,"syntology":null},{"url":"/paper/towards-anytime-optical-flow-estimation-with","slug":"towards-anytime-optical-flow-estimation-with","title":"Towards Anytime Optical Flow Estimation with Event Cameras","date":"2023-07-11","arxiv_id":"2307.05033","repositories_listed":1,"syntology":null},{"url":"/paper/parametric-depth-based-feature-representation","slug":"parametric-depth-based-feature-representation","title":"Parametric Depth Based Feature Representation Learning for Object Detection and Segmentation in Bird's Eye View","date":"2023-07-09","arxiv_id":"2307.04106","repositories_listed":1,"syntology":null},{"url":"/paper/safety-shielding-under-delayed-observation","slug":"safety-shielding-under-delayed-observation","title":"Safety Shielding under Delayed Observation","date":"2023-07-05","arxiv_id":"2307.02164","repositories_listed":1,"syntology":null},{"url":"/paper/fb-occ-3d-occupancy-prediction-based-on","slug":"fb-occ-3d-occupancy-prediction-based-on","title":"FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformation","date":"2023-07-04","arxiv_id":"2307.01492","repositories_listed":1,"syntology":null},{"url":"/paper/towards-building-self-aware-object-detectors-1","slug":"towards-building-self-aware-object-detectors-1","title":"Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration","date":"2023-07-03","arxiv_id":"2307.00934","repositories_listed":1,"syntology":null},{"url":"/paper/towards-safe-autonomous-driving-policies","slug":"towards-safe-autonomous-driving-policies","title":"Towards Safe Autonomous Driving Policies using a Neuro-Symbolic Deep Reinforcement Learning Approach","date":"2023-07-03","arxiv_id":"2307.01316","repositories_listed":1,"syntology":null},{"url":"/paper/intra-extra-source-exemplar-based-style","slug":"intra-extra-source-exemplar-based-style","title":"Intra- & Extra-Source Exemplar-Based Style Synthesis for Improved Domain Generalization","date":"2023-07-02","arxiv_id":"2307.00648","repositories_listed":1,"syntology":null},{"url":"/paper/mtr-multi-agent-motion-prediction-with","slug":"mtr-multi-agent-motion-prediction-with","title":"MTR++: Multi-Agent Motion Prediction with Symmetric Scene Modeling and Guided Intention Querying","date":"2023-06-30","arxiv_id":"2306.17770","repositories_listed":1,"syntology":null},{"url":"/paper/end-to-end-autonomous-driving-challenges-and","slug":"end-to-end-autonomous-driving-challenges-and","title":"End-to-end Autonomous Driving: Challenges and Frontiers","date":"2023-06-29","arxiv_id":"2306.16927","repositories_listed":1,"syntology":null},{"url":"/paper/communication-resources-constrained","slug":"communication-resources-constrained","title":"Communication Resources Constrained Hierarchical Federated Learning for End-to-End Autonomous Driving","date":"2023-06-28","arxiv_id":"2306.16169","repositories_listed":1,"syntology":null},{"url":"/paper/autograph-predicting-lane-graphs-from-traffic","slug":"autograph-predicting-lane-graphs-from-traffic","title":"AutoGraph: Predicting Lane Graphs from Traffic Observations","date":"2023-06-27","arxiv_id":"2306.15410","repositories_listed":1,"syntology":null},{"url":"/paper/panet-lidar-panoptic-segmentation-with-sparse","slug":"panet-lidar-panoptic-segmentation-with-sparse","title":"PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation","date":"2023-06-27","arxiv_id":"2306.15348","repositories_listed":1,"syntology":null},{"url":"/paper/ssc-rs-elevate-lidar-semantic-scene","slug":"ssc-rs-elevate-lidar-semantic-scene","title":"SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV Fusion","date":"2023-06-27","arxiv_id":"2306.15349","repositories_listed":1,"syntology":null},{"url":"/paper/symphonize-3d-semantic-scene-completion-with","slug":"symphonize-3d-semantic-scene-completion-with","title":"Symphonize 3D Semantic Scene Completion with Contextual Instance Queries","date":"2023-06-27","arxiv_id":"2306.15670","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":2,"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) · 1 unverified","sample_list":"/paper/symphonize-3d-semantic-scene-completion-with#ran","syntology_url":"https://syntology.ai/paper/2306.15670","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.15670"}},"official":{"repos":["hustvl/symphonies"],"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/interaction-aware-planning-with-deep-inverse","slug":"interaction-aware-planning-with-deep-inverse","title":"Interaction-Aware Planning With Deep Inverse Reinforcement Learning for Human-Like Autonomous Driving in Merge Scenarios","date":"2023-06-26","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/active-data-acquisition-in-autonomous-driving","slug":"active-data-acquisition-in-autonomous-driving","title":"Active Data Acquisition in Autonomous Driving Simulation","date":"2023-06-24","arxiv_id":"2306.13923","repositories_listed":1,"syntology":null},{"url":"/paper/state-wise-constrained-policy-optimization","slug":"state-wise-constrained-policy-optimization","title":"State-wise Constrained Policy Optimization","date":"2023-06-21","arxiv_id":"2306.12594","repositories_listed":1,"syntology":null},{"url":"/paper/rome-towards-large-scale-road-surface","slug":"rome-towards-large-scale-road-surface","title":"RoMe: Towards Large Scale Road Surface Reconstruction via Mesh Representation","date":"2023-06-20","arxiv_id":"2306.11368","repositories_listed":1,"syntology":null}],"record_sha256":"7be259caf612d93d14f70311ebe887a8533c36b3103acad0956d35da81cf247a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}