{"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/35","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":35,"pages_in_order":61,"rows_per_page":100,"rows":[3401,3500],"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/34","next":"/task/autonomous-driving/papers/36","papers":[{"url":null,"slug":"on-the-road-to-clarity-exploring-explainable","title":"On the Road to Clarity: Exploring Explainable AI for World Models in a Driver Assistance System","date":"2024-04-26","arxiv_id":"2404.17350","repositories_listed":0,"syntology":null},{"url":null,"slug":"integration-of-mixture-of-experts-and","title":"Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey","date":"2024-04-25","arxiv_id":"2404.16356","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-intermediate-fusion-methods-for","title":"A Survey on Intermediate Fusion Methods for Collaborative Perception Categorized by Real World Challenges","date":"2024-04-24","arxiv_id":"2404.16139","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-car-following-behaviors-using","title":"Learning Car-Following Behaviors Using Bayesian Matrix Normal Mixture Regression","date":"2024-04-24","arxiv_id":"2404.16023","repositories_listed":0,"syntology":null},{"url":null,"slug":"lanecorrect-self-supervised-lane-detection","title":"LaneCorrect: Self-supervised Lane Detection","date":"2024-04-23","arxiv_id":"2404.14671","repositories_listed":0,"syntology":null},{"url":null,"slug":"occgen-generative-multi-modal-3d-occupancy","title":"OccGen: Generative Multi-modal 3D Occupancy Prediction for Autonomous Driving","date":"2024-04-23","arxiv_id":"2404.15014","repositories_listed":0,"syntology":null},{"url":null,"slug":"collaborative-perception-datasets-in","title":"Collaborative Perception Datasets in Autonomous Driving: A Survey","date":"2024-04-22","arxiv_id":"2404.14022","repositories_listed":0,"syntology":null},{"url":null,"slug":"localization-based-on-mimo-backscattering","title":"Localization Based on MIMO Backscattering from Retro-Directive Antenna Arrays","date":"2024-04-22","arxiv_id":"2404.14206","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-radiance-field-in-autonomous-driving-a","title":"Neural Radiance Field in Autonomous Driving: A Survey","date":"2024-04-22","arxiv_id":"2404.13816","repositories_listed":0,"syntology":null},{"url":null,"slug":"pointdifformer-robust-point-cloud","title":"PointDifformer: Robust Point Cloud Registration With Neural Diffusion and Transformer","date":"2024-04-22","arxiv_id":"2404.14034","repositories_listed":0,"syntology":null},{"url":null,"slug":"soar-design-and-deployment-of-a-smart","title":"Soar: Design and Deployment of A Smart Roadside Infrastructure System for Autonomous Driving","date":"2024-04-21","arxiv_id":"2404.13786","repositories_listed":0,"syntology":null},{"url":null,"slug":"fisheyedetnet-object-detection-on-fisheye","title":"FisheyeDetNet: 360° Surround view Fisheye Camera based Object Detection System for Autonomous Driving","date":"2024-04-20","arxiv_id":"2404.13443","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-point-based-approach-to-efficient-lidar","title":"A Point-Based Approach to Efficient LiDAR Multi-Task Perception","date":"2024-04-19","arxiv_id":"2404.12798","repositories_listed":0,"syntology":null},{"url":null,"slug":"camera-agnostic-two-head-network-for-ego-lane","title":"Camera Agnostic Two-Head Network for Ego-Lane Inference","date":"2024-04-19","arxiv_id":"2404.12770","repositories_listed":0,"syntology":null},{"url":null,"slug":"dragtraffic-a-non-expert-interactive-and","title":"DragTraffic: Interactive and Controllable Traffic Scene Generation for Autonomous Driving","date":"2024-04-19","arxiv_id":"2404.12624","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-online-spatial-temporal-graph-trajectory","title":"An Online Spatial-Temporal Graph Trajectory Planner for Autonomous Vehicles","date":"2024-04-18","arxiv_id":"2404.12256","repositories_listed":0,"syntology":null},{"url":null,"slug":"reducing-bias-in-pre-trained-models-by-tuning","title":"Reducing Bias in Pre-trained Models by Tuning while Penalizing Change","date":"2024-04-18","arxiv_id":"2404.12292","repositories_listed":0,"syntology":null},{"url":null,"slug":"s4tp-social-suitable-and-safety-sensitive","title":"S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles","date":"2024-04-18","arxiv_id":"2404.11946","repositories_listed":0,"syntology":null},{"url":null,"slug":"stability-certificates-for-receding-horizon","title":"Stability Certificates for Receding Horizon Games","date":"2024-04-18","arxiv_id":"2404.12165","repositories_listed":0,"syntology":null},{"url":null,"slug":"tract-a-training-dynamics-aware-contrastive","title":"TrACT: A Training Dynamics Aware Contrastive Learning Framework for Long-tail Trajectory Prediction","date":"2024-04-18","arxiv_id":"2404.12538","repositories_listed":0,"syntology":null},{"url":null,"slug":"d-aug-enhancing-data-augmentation-for-dynamic","title":"D-Aug: Enhancing Data Augmentation for Dynamic LiDAR Scenes","date":"2024-04-17","arxiv_id":"2404.11127","repositories_listed":0,"syntology":null},{"url":null,"slug":"detector-collapse-backdooring-object","title":"Detector Collapse: Physical-World Backdooring Object Detection to Catastrophic Overload or Blindness in Autonomous Driving","date":"2024-04-17","arxiv_id":"2404.11357","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-dnn-robustness-against-adversarial","title":"Exploring DNN Robustness Against Adversarial Attacks Using Approximate Multipliers","date":"2024-04-17","arxiv_id":"2404.11665","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-to-deal-with-glare-for-improved","title":"How to deal with glare for improved perception of Autonomous Vehicles","date":"2024-04-17","arxiv_id":"2404.10992","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-3d-object-detection-on-unseen","title":"Multimodal 3D Object Detection on Unseen Domains","date":"2024-04-17","arxiv_id":"2404.11764","repositories_listed":0,"syntology":null},{"url":null,"slug":"tempbev-improving-learned-bev-encoders-with","title":"TempBEV: Improving Learned BEV Encoders with Combined Image and BEV Space Temporal Aggregation","date":"2024-04-17","arxiv_id":"2404.11803","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-evaluation-of-large-vision-language","title":"Automated Evaluation of Large Vision-Language Models on Self-driving Corner Cases","date":"2024-04-16","arxiv_id":"2404.10595","repositories_listed":0,"syntology":null},{"url":null,"slug":"end-to-end-training-and-testing-gamification","title":"End-To-End Training and Testing Gamification Framework to Learn Human Highway Driving","date":"2024-04-16","arxiv_id":"2404.10849","repositories_listed":0,"syntology":null},{"url":null,"slug":"laecips-large-vision-model-assisted-adaptive","title":"LAECIPS: Large Vision Model Assisted Adaptive Edge-Cloud Collaboration for IoT-based Embodied Intelligence System","date":"2024-04-16","arxiv_id":"2404.10498","repositories_listed":0,"syntology":null},{"url":null,"slug":"pregsu-a-generalized-traffic-scene","title":"PreGSU-A Generalized Traffic Scene Understanding Model for Autonomous Driving based on Pre-trained Graph Attention Network","date":"2024-04-16","arxiv_id":"2404.10263","repositories_listed":0,"syntology":null},{"url":null,"slug":"didlm-a-comprehensive-multi-sensor-dataset","title":"DIDLM: A SLAM Dataset for Difficult Scenarios Featuring Infrared, Depth Cameras, LIDAR, 4D Radar, and Others under Adverse Weather, Low Light Conditions, and Rough Roads","date":"2024-04-15","arxiv_id":"2404.09622","repositories_listed":0,"syntology":null},{"url":null,"slug":"sampling-for-model-predictive-trajectory","title":"Sampling for Model Predictive Trajectory Planning in Autonomous Driving using Normalizing Flows","date":"2024-04-15","arxiv_id":"2404.09657","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparseocc-rethinking-sparse-latent","title":"SparseOcc: Rethinking Sparse Latent Representation for Vision-Based Semantic Occupancy Prediction","date":"2024-04-15","arxiv_id":"2404.09502","repositories_listed":0,"syntology":null},{"url":null,"slug":"vfmm3d-releasing-the-potential-of-image-by","title":"VFMM3D: Releasing the Potential of Image by Vision Foundation Model for Monocular 3D Object Detection","date":"2024-04-15","arxiv_id":"2404.09431","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-fault-detection-for-large-language","title":"Evaluation and Improvement of Fault Detection for Large Language Models","date":"2024-04-14","arxiv_id":"2404.14419","repositories_listed":0,"syntology":null},{"url":null,"slug":"syntstereo2real-edge-aware-gan-for-remote","title":"SyntStereo2Real: Edge-Aware GAN for Remote Sensing Image-to-Image Translation while Maintaining Stereo Constraint","date":"2024-04-14","arxiv_id":"2404.09277","repositories_listed":0,"syntology":null},{"url":null,"slug":"d2e-an-autonomous-decision-making-dataset","title":"D2E-An Autonomous Decision-making Dataset involving Driver States and Human Evaluation","date":"2024-04-12","arxiv_id":"2406.01598","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-study-of-motion-transformer","title":"Transfer Learning Study of Motion Transformer-based Trajectory Predictions","date":"2024-04-12","arxiv_id":"2404.08271","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-detection-and-analysis-of-vehicles","title":"Real-Time Detection and Analysis of Vehicles and Pedestrians using Deep Learning","date":"2024-04-11","arxiv_id":"2404.08081","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-laneformer","title":"Sparse Laneformer","date":"2024-04-11","arxiv_id":"2404.07821","repositories_listed":0,"syntology":null},{"url":null,"slug":"vetrass-vehicle-trajectory-similarity-search","title":"VeTraSS: Vehicle Trajectory Similarity Search Through Graph Modeling and Representation Learning","date":"2024-04-11","arxiv_id":"2404.08021","repositories_listed":0,"syntology":null},{"url":null,"slug":"identification-of-fine-grained-systematic","title":"Identification of Fine-grained Systematic Errors via Controlled Scene Generation","date":"2024-04-10","arxiv_id":"2404.07045","repositories_listed":0,"syntology":null},{"url":null,"slug":"monocular-3d-lane-detection-for-autonomous","title":"Monocular 3D lane detection for Autonomous Driving: Recent Achievements, Challenges, and Outlooks","date":"2024-04-10","arxiv_id":"2404.06860","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparse-points-to-dense-clouds-enhancing-3d","title":"Sparse Points to Dense Clouds: Enhancing 3D Detection with Limited LiDAR Data","date":"2024-04-10","arxiv_id":"2404.06715","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparsead-sparse-query-centric-paradigm-for","title":"SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving","date":"2024-04-10","arxiv_id":"2404.06892","repositories_listed":0,"syntology":null},{"url":null,"slug":"agentscodriver-large-language-model-empowered","title":"AgentsCoDriver: Large Language Model Empowered Collaborative Driving with Lifelong Learning","date":"2024-04-09","arxiv_id":"2404.06345","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-insights-exploiting-structural","title":"Hierarchical Insights: Exploiting Structural Similarities for Reliable 3D Semantic Segmentation","date":"2024-04-09","arxiv_id":"2404.06124","repositories_listed":0,"syntology":null},{"url":null,"slug":"label-efficient-3d-object-detection-for-road","title":"Label-Efficient 3D Object Detection For Road-Side Units","date":"2024-04-09","arxiv_id":"2404.06256","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-autonomous-driving-with-small-scale","title":"Autonomous Driving Small-Scale Cars: A Survey of Recent Development","date":"2024-04-09","arxiv_id":"2404.06229","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-detection-from-4d-radar-data-in-low","title":"Human Detection from 4D Radar Data in Low-Visibility Field Conditions","date":"2024-04-08","arxiv_id":"2404.05307","repositories_listed":0,"syntology":null},{"url":null,"slug":"mose-boosting-vision-based-roadside-3d-object","title":"MOSE: Boosting Vision-based Roadside 3D Object Detection with Scene Cues","date":"2024-04-08","arxiv_id":"2404.05280","repositories_listed":0,"syntology":null},{"url":null,"slug":"residual-chain-prediction-for-autonomous","title":"Residual Chain Prediction for Autonomous Driving Path Planning","date":"2024-04-08","arxiv_id":"2404.05423","repositories_listed":0,"syntology":null},{"url":null,"slug":"unimix-towards-domain-adaptive-and","title":"UniMix: Towards Domain Adaptive and Generalizable LiDAR Semantic Segmentation in Adverse Weather","date":"2024-04-08","arxiv_id":"2404.05145","repositories_listed":0,"syntology":null},{"url":null,"slug":"light-the-night-a-multi-condition-diffusion","title":"Light the Night: A Multi-Condition Diffusion Framework for Unpaired Low-Light Enhancement in Autonomous Driving","date":"2024-04-07","arxiv_id":"2404.04804","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompting-multi-modal-tokens-to-enhance-end","title":"Prompting Multi-Modal Tokens to Enhance End-to-End Autonomous Driving Imitation Learning with LLMs","date":"2024-04-07","arxiv_id":"2404.04869","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-lane-change-behavior-prediction-and","title":"Automated Lane Change Behavior Prediction and Environmental Perception Based on SLAM Technology","date":"2024-04-06","arxiv_id":"2404.04492","repositories_listed":0,"syntology":null},{"url":null,"slug":"co-occ-coupling-explicit-feature-fusion-with","title":"Co-Occ: Coupling Explicit Feature Fusion with Volume Rendering Regularization for Multi-Modal 3D Semantic Occupancy Prediction","date":"2024-04-06","arxiv_id":"2404.04561","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-probabilistic-models-for-semi","title":"Exploring Probabilistic Models for Semi-supervised Learning","date":"2024-04-05","arxiv_id":"2404.04199","repositories_listed":0,"syntology":null},{"url":null,"slug":"scaling-motion-forecasting-models-with","title":"Scaling Motion Forecasting Models with Ensemble Distillation","date":"2024-04-05","arxiv_id":"2404.03843","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-methodology-to-study-the-impact-of-spiking","title":"A Methodology to Study the Impact of Spiking Neural Network Parameters considering Event-Based Automotive Data","date":"2024-04-04","arxiv_id":"2404.03493","repositories_listed":0,"syntology":null},{"url":null,"slug":"corp-a-multi-modal-dataset-for-campus","title":"CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks","date":"2024-04-04","arxiv_id":"2404.03191","repositories_listed":0,"syntology":null},{"url":null,"slug":"dendrites-endow-artificial-neural-networks","title":"Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning","date":"2024-04-04","arxiv_id":"2404.03708","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-guided-instance-aware-domain","title":"Language-Guided Instance-Aware Domain-Adaptive Panoptic Segmentation","date":"2024-04-04","arxiv_id":"2404.03799","repositories_listed":0,"syntology":null},{"url":null,"slug":"ad4rl-autonomous-driving-benchmarks-for","title":"AD4RL: Autonomous Driving Benchmarks for Offline Reinforcement Learning with Value-based Dataset","date":"2024-04-03","arxiv_id":"2404.02429","repositories_listed":0,"syntology":null},{"url":null,"slug":"tclc-gs-tightly-coupled-lidar-camera-gaussian","title":"TCLC-GS: Tightly Coupled LiDAR-Camera Gaussian Splatting for Autonomous Driving","date":"2024-04-03","arxiv_id":"2404.02410","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-latent-pathways-enhancing-the","title":"Exploring Latent Pathways: Enhancing the Interpretability of Autonomous Driving with a Variational Autoencoder","date":"2024-04-02","arxiv_id":"2404.01750","repositories_listed":0,"syntology":null},{"url":null,"slug":"heuristic-optimization-of-amplifier","title":"Heuristic Optimization of Amplifier Reconfiguration Process for Autonomous Driving Optical Networks","date":"2024-04-02","arxiv_id":"2404.01949","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-temporal-cues-by-predicting-objects","title":"Learning Temporal Cues by Predicting Objects Move for Multi-camera 3D Object Detection","date":"2024-04-02","arxiv_id":"2404.01580","repositories_listed":0,"syntology":null},{"url":null,"slug":"risk-aware-real-time-task-allocation-for","title":"Risk-Aware Real-Time Task Allocation for Stochastic Multi-Agent Systems under STL Specifications","date":"2024-04-02","arxiv_id":"2404.02111","repositories_listed":0,"syntology":null},{"url":null,"slug":"ml-kpi-prediction-in-5g-and-b5g-networks","title":"ML KPI Prediction in 5G and B5G Networks","date":"2024-04-01","arxiv_id":"2404.01530","repositories_listed":0,"syntology":null},{"url":null,"slug":"quad-query-based-interpretable-neural-motion","title":"QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving","date":"2024-04-01","arxiv_id":"2404.01486","repositories_listed":0,"syntology":null},{"url":null,"slug":"versatile-navigation-under-partial","title":"Versatile Navigation under Partial Observability via Value-guided Diffusion Policy","date":"2024-04-01","arxiv_id":"2404.02176","repositories_listed":0,"syntology":null},{"url":null,"slug":"adapting-to-length-shift-flexilength-network","title":"Adapting to Length Shift: FlexiLength Network for Trajectory Prediction","date":"2024-03-31","arxiv_id":"2404.00742","repositories_listed":0,"syntology":null},{"url":null,"slug":"denoising-low-dose-images-using-deep-learning","title":"Denoising Low-dose Images Using Deep Learning of Time Series Images","date":"2024-03-31","arxiv_id":"2404.00510","repositories_listed":0,"syntology":null},{"url":null,"slug":"survey-on-large-language-model-enhanced","title":"Survey on Large Language Model-Enhanced Reinforcement Learning: Concept, Taxonomy, and Methods","date":"2024-03-30","arxiv_id":"2404.00282","repositories_listed":0,"syntology":null},{"url":null,"slug":"ho-gaussian-hybrid-optimization-of-3d","title":"HO-Gaussian: Hybrid Optimization of 3D Gaussian Splatting for Urban Scenes","date":"2024-03-29","arxiv_id":"2403.20032","repositories_listed":0,"syntology":null},{"url":null,"slug":"ploc-a-new-evaluation-criterion-based-on","title":"PLoc: A New Evaluation Criterion Based on Physical Location for Autonomous Driving Datasets","date":"2024-03-29","arxiv_id":"2403.19893","repositories_listed":0,"syntology":null},{"url":null,"slug":"sgd-street-view-synthesis-with-gaussian","title":"SGD: Street View Synthesis with Gaussian Splatting and Diffusion Prior","date":"2024-03-29","arxiv_id":"2403.20079","repositories_listed":0,"syntology":null},{"url":null,"slug":"crkd-enhanced-camera-radar-object-detection","title":"CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation","date":"2024-03-28","arxiv_id":"2403.19104","repositories_listed":0,"syntology":null},{"url":null,"slug":"subjectdrive-scaling-generative-data-in","title":"SubjectDrive: Scaling Generative Data in Autonomous Driving via Subject Control","date":"2024-03-28","arxiv_id":"2403.19438","repositories_listed":0,"syntology":null},{"url":null,"slug":"genesis-rl-generating-natural-edge-cases-with","title":"GENESIS-RL: GEnerating Natural Edge-cases with Systematic Integration of Safety considerations and Reinforcement Learning","date":"2024-03-27","arxiv_id":"2403.19062","repositories_listed":0,"syntology":null},{"url":null,"slug":"long-and-short-term-constraints-driven-safe","title":"Long and Short-Term Constraints Driven Safe Reinforcement Learning for Autonomous Driving","date":"2024-03-27","arxiv_id":"2403.18209","repositories_listed":0,"syntology":null},{"url":null,"slug":"lord-large-models-based-opposite-reward","title":"LORD: Large Models based Opposite Reward Design for Autonomous Driving","date":"2024-03-27","arxiv_id":"2403.18965","repositories_listed":0,"syntology":null},{"url":null,"slug":"road-obstacle-detection-based-on-unknown","title":"Road Obstacle Detection based on Unknown Objectness Scores","date":"2024-03-27","arxiv_id":"2403.18207","repositories_listed":0,"syntology":null},{"url":null,"slug":"aide-an-automatic-data-engine-for-object","title":"AIDE: An Automatic Data Engine for Object Detection in Autonomous Driving","date":"2024-03-26","arxiv_id":"2403.17373","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-latency-neural-stereo-streaming","title":"Low-Latency Neural Stereo Streaming","date":"2024-03-26","arxiv_id":"2403.17879","repositories_listed":0,"syntology":null},{"url":null,"slug":"impact-of-video-compression-artifacts-on","title":"Impact of Video Compression Artifacts on Fisheye Camera Visual Perception Tasks","date":"2024-03-25","arxiv_id":"2403.16338","repositories_listed":0,"syntology":null},{"url":null,"slug":"proin-learning-to-predict-trajectory-based-on","title":"ProIn: Learning to Predict Trajectory Based on Progressive Interactions for Autonomous Driving","date":"2024-03-25","arxiv_id":"2403.16374","repositories_listed":0,"syntology":null},{"url":null,"slug":"synapse-learning-preferential-concepts-from","title":"SYNAPSE: SYmbolic Neural-Aided Preference Synthesis Engine","date":"2024-03-25","arxiv_id":"2403.16689","repositories_listed":0,"syntology":null},{"url":null,"slug":"synfog-a-photo-realistic-synthetic-fog","title":"SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Driving","date":"2024-03-25","arxiv_id":"2403.17094","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-nerfs-ready-for-autonomous-driving","title":"Are NeRFs ready for autonomous driving? Towards closing the real-to-simulation gap","date":"2024-03-24","arxiv_id":"2403.16092","repositories_listed":0,"syntology":null},{"url":null,"slug":"engineering-safety-requirements-for","title":"Engineering Safety Requirements for Autonomous Driving with Large Language Models","date":"2024-03-24","arxiv_id":"2403.16289","repositories_listed":0,"syntology":null},{"url":"/paper/pvalane-prior-guided-3d-lane-detection-with","slug":"pvalane-prior-guided-3d-lane-detection-with","title":"PVALane: Prior-Guided 3D Lane Detection with View-Agnostic Feature Alignment","date":"2024-03-24","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-multi-frame-neural-scene-flow","title":"Self-Supervised Multi-Frame Neural Scene Flow","date":"2024-03-24","arxiv_id":"2403.16116","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatio-temporal-bi-directional-cross-frame","title":"Spatio-Temporal Bi-directional Cross-frame Memory for Distractor Filtering Point Cloud Single Object Tracking","date":"2024-03-23","arxiv_id":"2403.15831","repositories_listed":0,"syntology":null},{"url":null,"slug":"augmented-reality-based-simulated-data-arsim","title":"Augmented Reality based Simulated Data (ARSim) with multi-view consistency for AV perception networks","date":"2024-03-22","arxiv_id":"2403.15370","repositories_listed":0,"syntology":null},{"url":null,"slug":"autonomous-driving-with-perception","title":"Autonomous Driving With Perception Uncertainties: Deep-Ensemble Based Adaptive Cruise Control","date":"2024-03-22","arxiv_id":"2403.15577","repositories_listed":0,"syntology":null},{"url":null,"slug":"tri-perspective-view-decomposition-for","title":"Tri-Perspective View Decomposition for Geometry-Aware Depth Completion","date":"2024-03-22","arxiv_id":"2403.15008","repositories_listed":0,"syntology":null},{"url":null,"slug":"application-of-tensorized-neural-networks-for","title":"Application of Tensorized Neural Networks for Cloud Classification","date":"2024-03-21","arxiv_id":"2405.10946","repositories_listed":0,"syntology":null},{"url":null,"slug":"surroundsdf-implicit-3d-scene-understanding","title":"SurroundSDF: Implicit 3D Scene Understanding Based on Signed Distance Field","date":"2024-03-21","arxiv_id":"2403.14366","repositories_listed":0,"syntology":null}],"record_sha256":"73be666be787a4561d12740b1cedf696f466f67d00626cf673ef921d9458c16d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}