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/zhouqiu/sogdet

공식 코드

SOGDet: Semantic-Occupancy Guided Multi-view 3D Object Detection

https://github.com/zhourobotics/reasondrive

공식 코드

ReasonDrive: Efficient Visual Question Answering for Autonomous Vehicles with Reasoning-Enhanced Small Vision-Language Models

https://github.com/zhouzheyuan/sgm3d

공식 코드

SGM3D: Stereo Guided Monocular 3D Object Detection

https://github.com/zhujunli1993/swindepose

공식 코드

Depth-based 6DoF Object Pose Estimation using Swin Transformer

https://github.com/zhuliwen/roadnetsz

공식 코드

MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal Control

https://github.com/zhumorui/m3cad

공식 코드

M3CAD: Towards Generic Cooperative Autonomous Driving Benchmark

https://github.com/zhuoinoulu/svnet

공식 코드

SVNet: Where SO(3) Equivariance Meets Binarization on Point Cloud Representation

https://github.com/zhuxing0/sa-radar

공식 코드

Simulate Any Radar: Attribute-Controllable Radar Simulation via Waveform Parameter Embedding

https://github.com/zilin-huang/HAIM-DRL

공식 코드

HAIM-DRL: Enhanced Human-in-the-loop Reinforcement Learning for Safe and Efficient Autonomous Driving

https://github.com/zilin-huang/PE-RLHF

공식 코드

Trustworthy Human-AI Collaboration: Reinforcement Learning with Human Feedback and Physics Knowledge for Safe Autonomous Driving

https://github.com/zillur-av/LVLane

공식 코드

LVLane: Deep Learning for Lane Detection and Classification in Challenging Conditions

https://github.com/ziongo6/fadet

공식 코드

FADet: A Multi-sensor 3D Object Detection Network based on Local Featured Attention

https://github.com/ziongo6/hawkdrive

공식 코드

HawkDrive: A Transformer-driven Visual Perception System for Autonomous Driving in Night Scene

https://github.com/zippiest/yolo-cca

공식 코드

YOLO-CCA: A Context-Based Approach for Traffic Sign Detection

https://github.com/ziqipang/lm4visualencoding

공식 코드

Frozen Transformers in Language Models Are Effective Visual Encoder Layers

https://github.com/ziqipang/streamingforecasting

공식 코드

Streaming Motion Forecasting for Autonomous Driving

https://github.com/ziquanliu/ICML2024-AT-UR

공식 코드

The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks

https://github.com/zirui0625/difiisr

공식 코드

DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-Resolution

https://github.com/ziweiwwang/AEB-Tracker

공식 코드

Asynchronous Blob Tracker for Event Cameras

https://github.com/ziweiwwang/event-blob-tracking

공식 코드

Asynchronous Blob Tracker for Event Cameras

https://github.com/zju-fast-lab/fsgp_bgk

공식 코드

Real-time Spatial-temporal Traversability Assessment via Feature-based Sparse Gaussian Process

https://github.com/zju-fast-lab/radar-diffusion

공식 코드

Towards Dense and Accurate Radar Perception Via Efficient Cross-Modal Diffusion Model

https://github.com/zju3dv/DeFlowSLAM

공식 코드

D$^3$FlowSLAM: Self-Supervised Dynamic SLAM with Flow Motion Decomposition and DINO Guidance

https://github.com/zju3dv/street_gaussians

공식 코드

Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting

https://github.com/zjunlp/easyedit

공식 코드

ADS-Edit: A Multimodal Knowledge Editing Dataset for Autonomous Driving Systems

https://github.com/zkyseu/O2SFormer

공식 코드

End-to-End Lane detection with One-to-Several Transformer

https://github.com/zl-helios/trajpac

공식 코드

TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models

https://github.com/zlatanajanovic/SBMP_PerfDriving

공식 코드

Search-Based Task and Motion Planning for Hybrid Systems: Agile Autonomous Vehicles

https://github.com/zlichen/ppad

공식 코드

PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Driving

https://github.com/zlr20/saferl_kit

공식 코드

SafeRL-Kit: Evaluating Efficient Reinforcement Learning Methods for Safe Autonomous Driving

https://github.com/zminton/TrolleyMod

공식 코드

TrolleyMod v1.0: An Open-Source Simulation and Data-Collection Platform for Ethical Decision Making in Autonomous Vehicles

https://github.com/zohreh-aaa/dnn-testing

공식 코드

Black-Box Testing of Deep Neural Networks Through Test Case Diversity

https://github.com/zongdai/EditingForDNN

공식 코드

Fine-Grained Vehicle Perception via 3D Part-Guided Visual Data Augmentation

https://github.com/zongdai/autoshape

공식 코드

AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

https://github.com/zouxianghong/LifelongPR

공식 코드

LifelongPR: Lifelong knowledge fusion for point cloud place recognition based on replay and prompt learning

https://github.com/zplusdragon/plip

공식 코드

PLIP: Language-Image Pre-training for Person Representation Learning

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