Papers with Code 아카이브

Autonomous Driving

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 6
평가표: 4
보존된 평가 기록: 23

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/rstless-research/ncod-learning-with-noisy-labels

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Learning with Noisy Labels through Learnable Weighting and Centroid Similarity

https://github.com/ruanyudi/ecaformer

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ECAFormer: Low-light Image Enhancement using Cross Attention

https://github.com/rubbish001/co-fix3d

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Co-Fix3D: Enhancing 3D Object Detection with Collaborative Refinement

https://github.com/rui-qian/SoTA-3D-Object-Detection

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3D Object Detection for Autonomous Driving: A Survey

https://github.com/ruili3/dynamic-multiframe-depth

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Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes

https://github.com/ruipingl/skr_pea

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TransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation

https://github.com/ruipingl/transkd

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TransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation

https://github.com/ruiyum/stone

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STONE: A Submodular Optimization Framework for Active 3D Object Detection

https://github.com/runjian-chen/co3

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CO^3: Cooperative Unsupervised 3D Representation Learning for Autonomous Driving

https://github.com/rwightman/pytorch-image-models

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EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction

https://github.com/saferl-lab/safe-marl-in-autonomous-driving

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Safe Multi-Agent Reinforcement Learning with Bilevel Optimization in Autonomous Driving

https://github.com/sainingzhang/uc-gs

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Drone-assisted Road Gaussian Splatting with Cross-view Uncertainty

https://github.com/sakharok13/x-ray-teacher-patching-tools

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Weak-to-Strong 3D Object Detection with X-Ray Distillation

https://github.com/salmank255/ROAD_Waymo_Baseline

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ROAD-Waymo: Action Awareness at Scale for Autonomous Driving

https://github.com/saltoricristiano/cosmix-uda

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CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation

https://github.com/saltoricristiano/gipso-sfouda

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GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation

https://github.com/samedyalcin/mrad

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Impact of Surface Reflections in Maritime Obstacle Detection

https://github.com/sampo-kuutti/adversarial-mixture-density-networks

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Adversarial Mixture Density Networks: Learning to Drive Safely from Collision Data

https://github.com/sampo-kuutti/training-adversarial-agents

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Training Adversarial Agents to Exploit Weaknesses in Deep Control Policies

https://github.com/samuelmallick/mpcrl-vehicle-gears

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Learning-Based MPC for Fuel Efficient Control of Autonomous Vehicles with Discrete Gear Selection

https://github.com/sancarlim/explainable-mp

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Towards Explainable Motion Prediction using Heterogeneous Graph Representations

https://github.com/sanjay-810/aydiv2

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AYDIV: Adaptable Yielding 3D Object Detection via Integrated Contextual Vision Transformer

https://github.com/sanjay-810/savid

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SaViD: Spectravista Aesthetic Vision Integration for Robust and Discerning 3D Object Detection in Challenging Environments

https://github.com/sanmin0312/P2D

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Predict to Detect: Prediction-guided 3D Object Detection using Sequential Images

https://github.com/sapirkontente/clrmatchnet

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CLRmatchNet: Enhancing Curved Lane Detection with Deep Matching Process

https://github.com/sbysbysbys/afov

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3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving

https://github.com/sbysbysbys/uov

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3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving

https://github.com/schko/fixatt

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Gaze-Informed Vision Transformers: Predicting Driving Decisions Under Uncertainty

https://github.com/schmidt-ju/argoverse-navmap

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Exploring Navigation Maps for Learning-Based Motion Prediction

https://github.com/schmidt-ju/crat-pred

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CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph Convolutional Neural Networks and Multi-Head Self-Attention

https://github.com/scnu-rislab/cv-mos

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CV-MOS: A Cross-View Model for Motion Segmentation

https://github.com/scnu-rislab/kdmos

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KDMOS:Knowledge Distillation for Motion Segmentation

https://github.com/scnu-rislab/mambaflow

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MambaFlow: A Novel and Flow-guided State Space Model for Scene Flow Estimation

https://github.com/scnu-rislab/mf-mos

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MF-MOS: A Motion-Focused Model for Moving Object Segmentation

https://github.com/scope-lab-vu/anti-carla

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ANTI-CARLA: An Adversarial Testing Framework for Autonomous Vehicles in CARLA

https://github.com/sdqesdataset/sdqes_generation

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Streaming Detection of Queried Event Start

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