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/jessicamecht/concept_gridlock

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Driving through the Concept Gridlock: Unraveling Explainability Bottlenecks in Automated Driving

https://github.com/jiachengzuo/ralad

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RALAD: Bridging the Real-to-Sim Domain Gap in Autonomous Driving with Retrieval-Augmented Learning

https://github.com/jiahaoljh/mapvectorizationevaltoolkit

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Online Map Vectorization for Autonomous Driving: A Rasterization Perspective

https://github.com/jialeli1/lidarseg3d

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MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Driving

https://github.com/jialewei/onebev

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OneBEV: Using One Panoramic Image for Bird's-Eye-View Semantic Mapping

https://github.com/jiamiya/HOPE

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HOPE: A Reinforcement Learning-based Hybrid Policy Path Planner for Diverse Parking Scenarios

https://github.com/jiangchaokang/3dsflabelling

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3DSFLabelling: Boosting 3D Scene Flow Estimation by Pseudo Auto-labelling

https://github.com/jiangchaokang/neurogauss4d-pci

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NeuroGauss4D-PCI: 4D Neural Fields and Gaussian Deformation Fields for Point Cloud Interpolation

https://github.com/jianglongye/implicit-tracking

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Online Adaptation for Implicit Object Tracking and Shape Reconstruction in the Wild

https://github.com/jiangxb98/mwsis-plugin

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MWSIS: Multimodal Weakly Supervised Instance Segmentation with 2D Box Annotations for Autonomous Driving

https://github.com/jiashunwang/MRT

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Multi-Person 3D Motion Prediction with Multi-Range Transformers

https://github.com/jiayuanwang-jw/yolov8-multi-task

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You Only Look at Once for Real-time and Generic Multi-Task

https://github.com/jiayuzou2020/diffbev

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DiffBEV: Conditional Diffusion Model for Bird's Eye View Perception

https://github.com/jiayuzou2020/hft

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HFT: Lifting Perspective Representations via Hybrid Feature Transformation

https://github.com/jieqianyu/panet

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PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation

https://github.com/jieqianyu/sgn

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Camera-based 3D Semantic Scene Completion with Sparse Guidance Network

https://github.com/jieqianyu/ssc-rs

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SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV Fusion

https://github.com/jimmy9704/gps-glass

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GPS-GLASS: Learning Nighttime Semantic Segmentation Using Daytime Video and GPS data

https://github.com/jimmyzou/snipper

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Snipper: A Spatiotemporal Transformer for Simultaneous Multi-Person 3D Pose Estimation Tracking and Forecasting on a Video Snippet

https://github.com/jinghanY/physicalAttackImageComposition

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Finding Physical Adversarial Examples for Autonomous Driving with Fast and Differentiable Image Compositing

https://github.com/jingkang50/oodsurvey

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Generalized Out-of-Distribution Detection: A Survey

https://github.com/jingkang50/openood

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Generalized Out-of-Distribution Detection: A Survey

https://github.com/jinlong17/da-detect

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Domain Adaptive Object Detection for Autonomous Driving under Foggy Weather

https://github.com/jinyuanliu-cv/segmif

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Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation

https://github.com/jlchen-c/occprophet

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OccProphet: Pushing Efficiency Frontier of Camera-Only 4D Occupancy Forecasting with Observer-Forecaster-Refiner Framework

https://github.com/jlubars/RL-MPC-LaneMerging

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Combining Reinforcement Learning with Model Predictive Control for On-Ramp Merging

https://github.com/jmiemirza/dilam

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Sit Back and Relax: Learning to Drive Incrementally in All Weather Conditions

https://github.com/jmiemirza/dua

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The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by Normalization

https://github.com/jmoonr/dv-3dlane

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DV-3DLane: End-to-end Multi-modal 3D Lane Detection with Dual-view Representation

https://github.com/jmoonr/latr

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LATR: 3D Lane Detection from Monocular Images with Transformer

https://github.com/johnsonjiang1996/awesome-vla4ad

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A Survey on Vision-Language-Action Models for Autonomous Driving

https://github.com/jokester-zzz/ssa-sc

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Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds

https://github.com/jonguti13/parameterprotection

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Evaluating Single Event Upsets in Deep Neural Networks for Semantic Segmentation: an embedded system perspective

https://github.com/jonguti13/tensorfi2

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Evaluating Single Event Upsets in Deep Neural Networks for Semantic Segmentation: an embedded system perspective

https://github.com/joonh-kim/etm

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Continual Unsupervised Domain Adaptation for Semantic Segmentation

https://github.com/joy-driven/granp

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GRANP: A Graph Recurrent Attentive Neural Process Model for Vehicle Trajectory Prediction

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.