Papers with Code 아카이브

Autonomous Vehicles

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크: 15
평가표: 1
보존된 평가 기록: 2

Autonomous vehicles is the task of making a vehicle that can guide itself 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: 0.6">( Image credit: GSNet: Joint Vehicle Pose and Shape Reconstruction with Geometrical and Scene-aware Supervision )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/fudan-zvg/realengine

공식 코드

RealEngine: Simulating Autonomous Driving in Realistic Context

https://github.com/fudan-zvg/realmotion

공식 코드

Motion Forecasting in Continuous Driving

https://github.com/fudan-zvg/reason2drive

공식 코드

Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving

https://github.com/fudan-zvg/roadnet

공식 코드

LaneGraph2Seq: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity Enhancement

https://github.com/fudan-zvg/wovogen

공식 코드

WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation

https://github.com/fuhaha824/pg-attack

공식 코드

PG-Attack: A Precision-Guided Adversarial Attack Framework Against Vision Foundation Models for Autonomous Driving

https://github.com/fujiawei0724/interactionnet

공식 코드

InteractionNet: Joint Planning and Prediction for Autonomous Driving with Transformers

https://github.com/funcdecl/df-slam

공식 코드

DF-SLAM: Dictionary Factors Representation for High-Fidelity Neural Implicit Dense Visual SLAM System

https://github.com/fuxiao0719/panopticnerf

공식 코드

PanopticNeRF-360: Panoramic 3D-to-2D Label Transfer in Urban Scenes

https://github.com/fwesterhout/Smooth-Trajectron

공식 코드

Smooth-Trajectron++: Augmenting the Trajectron++ behaviour prediction model with smooth attention

https://github.com/fy-vision/loopda

공식 코드

LoopDA: Constructing Self-loops to Adapt Nighttime Semantic Segmentation

https://github.com/fzhiheng/RoGS

공식 코드

RoGs: Large Scale Road Surface Reconstruction with Meshgrid Gaussian

https://github.com/fzi-forschungszentrum-informatik/NNAD

공식 코드

Object Tracking by Detection with Visual and Motion Cues

https://github.com/fzi-forschungszentrum-informatik/anovox

공식 코드

AnoVox: A Benchmark for Multimodal Anomaly Detection in Autonomous Driving

https://github.com/fzi-forschungszentrum-informatik/fadm

공식 코드

Context-Aware Full Body Anonymization using Text-to-Image Diffusion Models

https://github.com/fzi-forschungszentrum-informatik/informed_rl

공식 코드

Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptions

https://github.com/fzi-forschungszentrum-informatik/muvo

공식 코드

MUVO: A Multimodal World Model with Spatial Representations for Autonomous Driving

https://github.com/fzi-forschungszentrum-informatik/quantification_road_user_behavior/blob/main/README.md

공식 코드

Quantification of Actual Road User Behavior on the Basis of Given Traffic Rules

https://github.com/g-meghana-reddy/open-world-panoptic-segmentation

공식 코드

Lidar Panoptic Segmentation in an Open World

https://github.com/gabriel-vanzandycke/deepsport

공식 코드

Context-Aware 3D Object Localization from Single Calibrated Images: A Study of Basketballs

https://github.com/galaxy-zrx/edgehead

공식 코드

Detect Closer Surfaces that can be Seen: New Modeling and Evaluation in Cross-domain 3D Object Detection

https://github.com/gandolfczjh/3d2fool

공식 코드

Physical 3D Adversarial Attacks against Monocular Depth Estimation in Autonomous Driving

https://github.com/ganglii/devsafety

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A Retention-Centric Framework for Continual Learning with Guaranteed Model Developmental Safety

https://github.com/ganwanshui/simpleoccupancy

공식 코드

A Simple Framework for 3D Occupancy Estimation in Autonomous Driving

https://github.com/gaoyinfeng/piwm

공식 코드

Dream to Drive with Predictive Individual World Model

https://github.com/gaperezsa/3deformrs

공식 코드

3DeformRS: Certifying Spatial Deformations on Point Clouds

https://github.com/garfield-cpp/hgsfusion

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HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection

https://github.com/garrickbrazil/M3D-RPN

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M3D-RPN: Monocular 3D Region Proposal Network for Object Detection

https://github.com/gaurav00700/selfsupervised-nvsf

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Self-Supervised Multimodal NeRF for Autonomous Driving

https://github.com/gaussianer/fasterseg

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Semantic Segmentation for Autonomous Driving: Model Evaluation, Dataset Generation, Perspective Comparison, and Real-Time Capability

https://github.com/ge25nab/Awesome-VLM-AD-ITS

공식 코드

Vision Language Models in Autonomous Driving: A Survey and Outlook

https://github.com/gengshan-y/monodepth-uncertainty

공식 코드

Inferring Distributions Over Depth from a Single Image

https://github.com/geoai4cities/pgs-cam

공식 코드

Towards Explainable LiDAR Point Cloud Semantic Segmentation via Gradient Based Target Localization

https://github.com/geoaigroup/geoai-ecrs2023

공식 코드

Trainable Noise Model as an XAI evaluation method: application on Sobol for remote sensing image segmentation

https://github.com/georgeeskandar/towards-pragmatic-semantic-image-synthesis-for-urban-scenes

공식 코드

Towards Pragmatic Semantic Image Synthesis for Urban Scenes

https://github.com/georgeliu233/scene-rep-transformer

공식 코드

Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous Driving

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