Papers with Code 아카이브
Autonomous Driving
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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Autonomous driving is the task of driving a vehicle without human conduction.
Many of the state-of-the-art results can be found at more general task pages such as 3D Object Detection and Semantic Segmentation.
<span style="color:grey; opacity: 0.5">(Image credit: Exploring the Limitations of Behavior Cloning for Autonomous Driving)</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ziweiwwang/event-blob-tracking
공식 코드https://github.com/zju3dv/street_gaussians
공식 코드Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting
https://github.com/zjunlp/easyedit
공식 코드ADS-Edit: A Multimodal Knowledge Editing Dataset for Autonomous Driving Systems
https://github.com/zlatanajanovic/SBMP_PerfDriving
공식 코드Search-Based Task and Motion Planning for Hybrid Systems: Agile Autonomous Vehicles
https://github.com/zlichen/ppad
공식 코드PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving
https://github.com/zlr20/saferl_kit
공식 코드SafeRL-Kit: Evaluating Efficient Reinforcement Learning Methods for Safe Autonomous Driving
https://github.com/zohreh-aaa/dnn-testing
공식 코드Black-Box Testing of Deep Neural Networks Through Test Case Diversity
https://github.com/zongdai/EditingForDNN
공식 코드Fine-Grained Vehicle Perception via 3D Part-Guided Visual Data Augmentation
https://github.com/zongdai/autoshape
공식 코드AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection
https://github.com/zouxianghong/LifelongPR
공식 코드https://github.com/zrfreya/AutoRemover
공식 코드AutoRemover: Automatic Object Removal for Autonomous Driving Videos
https://github.com/zrrskywalker/monodetr
공식 코드MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection
https://github.com/ztsrxh/roadbev
공식 코드https://github.com/zubair-irshad/Awesome-Implicit-NeRF-Robotics
공식 코드https://github.com/zuosc19/gaussianworld
공식 코드GaussianWorld: Gaussian World Model for Streaming 3D Occupancy Prediction
https://github.com/zuosc19/quadricformer
공식 코드QuadricFormer: Scene as Superquadrics for 3D Semantic Occupancy Prediction
https://github.com/zuzuba/CISR_NeurIPS20
공식 코드https://github.com/zya3d/awesome-3d-occupancy-prediction
공식 코드Vision-based 3D occupancy prediction in autonomous driving: a review and outlook
https://github.com/zyangchen/mocha-stereo
공식 코드Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph
https://github.com/zympsyche/bevworld
공식 코드BEVWorld: A Multimodal World Model for Autonomous Driving via Unified BEV Latent Space
https://github.com/zzj403/BEV_Robust
공식 코드https://github.com/zzy-zhou/dsec-mos
공식 코드Event-Free Moving Object Segmentation from Moving Ego Vehicle
https://github.com/zzy-zhou/renet
공식 코드RGB-Event Fusion for Moving Object Detection in Autonomous Driving
https://gitlab.au.dk/maleci/opendr/ua-ab3dmot
공식 코드Uncertainty-Aware AB3DMOT by Variational 3D Object Detection
https://gitlab.au.dk/maleci/opendr/variational-voxel-3d-detetction
공식 코드https://gitlab.au.dk/maleci/opendr/vnn_vpit_opendr
공식 코드https://gitlab.com/aksoyeren/salsanet
공식 코드SalsaNet: Fast Road and Vehicle Segmentation in LiDAR Point Clouds for Autonomous Driving
https://gitlab.com/peroyose/radial_prediction_layers
공식 코드https://gitlab.com/sumo-rl/sumo_openai_gym
공식 코드Urban Driving with Multi-Objective Deep Reinforcement Learning
https://zenodo.org/record/12611978
공식 코드MMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor Perception
https://bitbucket.org/fafz/stein_particle_filter
Stein ICP for Uncertainty Estimation in Point Cloud Matching
https://dagshub.com/arnavr.neo/YOLOX
https://gitee.com/gai-shaoyan/mind3d
PointPillars: Fast Encoders for Object Detection from Point Clouds
https://github.com/15526837635/CenterPoint
https://github.com/1hb6s7t/MindSpore-Uncertainty_Calibration_Object_Detection-
A Theoretical and Practical Framework for Evaluating Uncertainty Calibration in Object Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.