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/aldahdooh/detectors_review

공식 코드

Adversarial Example Detection for DNN Models: A Review and Experimental Comparison

https://github.com/aldipiroli/semantic_spray_dataset

공식 코드

Energy-based Detection of Adverse Weather Effects in LiDAR Data

https://github.com/alejandrofontan/vslam-lab

공식 코드

VSLAM-LAB: A Comprehensive Framework for Visual SLAM Methods and Datasets

https://github.com/alelevente/felesh

공식 코드

A V2X-based Privacy Preserving Federated Measuring and Learning System

https://github.com/alex-1337/lanetca

공식 코드

LaneTCA: Enhancing Video Lane Detection with Temporal Context Aggregation

https://github.com/alexanderswerdlow/BEVGen

공식 코드

Street-View Image Generation from a Bird's-Eye View Layout

https://github.com/alexmelekhin/mssplace

공식 코드

MSSPlace: Multi-Sensor Place Recognition with Visual and Text Semantics

https://github.com/alextimans/conformal-od

공식 코드

Adaptive Bounding Box Uncertainties via Two-Step Conformal Prediction

https://github.com/alfredgu001324/MapBEVPrediction

공식 코드

Accelerating Online Mapping and Behavior Prediction via Direct BEV Feature Attention

https://github.com/alfredgu001324/mapuncertaintyprediction

공식 코드

Producing and Leveraging Online Map Uncertainty in Trajectory Prediction

https://github.com/alibaba/easyrobust

공식 코드

COCO-O: A Benchmark for Object Detectors under Natural Distribution Shifts

https://github.com/alik033/lit-net

공식 코드

Harnessing Multi-resolution and Multi-scale Attention for Underwater Image Restoration

https://github.com/aliyun/conditional-lane-detection

공식 코드

CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution

https://github.com/allen-adastra/risk_assess

공식 코드

Fast Risk Assessment for Autonomous Vehicles Using Learned Models of Agent Futures

https://github.com/allenchen1998/rad

공식 코드

Relevance Attack on Detectors

https://github.com/alniyatrui/cafe-ad

공식 코드

CAFE-AD: Cross-Scenario Adaptive Feature Enhancement for Trajectory Planning in Autonomous Driving

https://github.com/alphaplustt/daocc

공식 코드

DAOcc: 3D Object Detection Assisted Multi-Sensor Fusion for 3D Occupancy Prediction

https://github.com/alshami52/COOOL_benchmark

공식 코드

COOOL: Challenge Of Out-Of-Label A Novel Benchmark for Autonomous Driving

https://github.com/alshedivat/keras-gp

공식 코드

Learning Scalable Deep Kernels with Recurrent Structure

https://github.com/alshedivat/kgp

공식 코드

Learning Scalable Deep Kernels with Recurrent Structure

https://github.com/alterpang/multi_orb_slam

공식 코드

Multicam-SLAM: Non-overlapping Multi-camera SLAM for Indirect Visual Localization and Navigation

https://github.com/alvariseppanen/4denoisenet

공식 코드

4DenoiseNet: Adverse Weather Denoising from Adjacent Point Clouds

https://github.com/alvariseppanen/smednet

공식 코드

Multi-Echo Denoising in Adverse Weather

https://github.com/amai-gsu/mambev

공식 코드

MamBEV: Enabling State Space Models to Learn Birds-Eye-View Representations

https://github.com/amaralibey/mixvpr

공식 코드

MixVPR: Feature Mixing for Visual Place Recognition

https://github.com/amir-ni/trajectory-prediction

공식 코드

TrajLearn: Trajectory Prediction Learning using Deep Generative Models

https://github.com/amirhosseinzlf/smarla

공식 코드

SMARLA: A Safety Monitoring Approach for Deep Reinforcement Learning Agents

https://github.com/amirhosseinzlf/starla

공식 코드

A Search-Based Testing Approach for Deep Reinforcement Learning Agents

https://github.com/amnondrory/lidarregistration

공식 코드

Stress-Testing Point Cloud Registration on Automotive LiDAR

https://github.com/amro-kamal/objectpose

공식 코드

Progress and limitations of deep networks to recognize objects in unusual poses

https://github.com/amsterdam-internships/self-learning-traffic-lights

공식 코드

Back to Basics: Deep Reinforcement Learning in Traffic Signal Control

https://github.com/amy-choi/AttackDefenseYOLO

공식 코드

Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving Scenarios

https://github.com/andreaceccarelli/metrics_model

공식 코드

Evaluating Object (mis)Detection from a Safety and Reliability Perspective: Discussion and Measures

https://github.com/andreaconti/lidar-confidence

공식 코드

Unsupervised confidence for LiDAR depth maps and applications

https://github.com/andrewcaunes/ia4markings

공식 코드

seg_3D_by_PC2D: Multi-View Projection for Domain Generalization and Adaptation in 3D Semantic Segmentation

https://github.com/andyj1/doubly-contrastive-semseg

공식 코드

Doubly Contrastive End-to-End Semantic Segmentation for Autonomous Driving under Adverse Weather

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