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/seawee1/driver-dojo

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Driver Dojo: A Benchmark for Generalizable Reinforcement Learning for Autonomous Driving

https://github.com/selflein/ma-ebm

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Master's Thesis: Out-of-distribution Detection with Energy-based Models

https://github.com/senakicir/keyposeprediction

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Long Term Motion Prediction Using Keyposes

https://github.com/sense-gvt/fast-bev

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Fast-BEV: Towards Real-time On-vehicle Bird's-Eye View Perception

https://github.com/sensetime-fvg/opendwm

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UniMLVG: Unified Framework for Multi-view Long Video Generation with Comprehensive Control Capabilities for Autonomous Driving

https://github.com/sephirex-x/latentdriver

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Learning Multiple Probabilistic Decisions from Latent World Model in Autonomous Driving

https://github.com/sercant/mobile-segmentation

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An efficient solution for semantic segmentation: ShuffleNet V2 with atrous separable convolutions

https://github.com/serenos/lwsis

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LWSIS: LiDAR-guided Weakly Supervised Instance Segmentation for Autonomous Driving

https://github.com/seungwonoh5/Adversarial_Attacks_against_Object_Detection

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Resilience of Autonomous Vehicle Object Category Detection to Universal Adversarial Perturbations

https://github.com/shachoi/RobustNet

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RobustNet: Improving Domain Generalization in Urban-Scene Segmentation via Instance Selective Whitening

https://github.com/shahin-01/vqa-ad

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Explaining Autonomous Driving Actions with Visual Question Answering

https://github.com/shalfun/DrivingDiffusion

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DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model

https://github.com/shangweihung/LDFNet

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Incorporating Luminance, Depth and Color Information by a Fusion-based Network for Semantic Segmentation

https://github.com/shanjiayao/ptt

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Real-time 3D Single Object Tracking with Transformer

https://github.com/shanwang-shan/homofusion

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Homography Guided Temporal Fusion for Road Line and Marking Segmentation

https://github.com/shaoqing26/fusionpainting

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FusionPainting: Multimodal Fusion with Adaptive Attention for 3D Object Detection

https://github.com/shark0-0/vg4d

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VG4D: Vision-Language Model Goes 4D Video Recognition

https://github.com/shenqildr/ScorNet

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A Robust and Reliable Point Cloud Recognition Network Under Rigid Transformation

https://github.com/sherwinbahmani/ynet_adaptive

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Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective

https://github.com/shifts-project/shifts

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Shifts 2.0: Extending The Dataset of Real Distributional Shifts

https://github.com/shilinyan99/panovos

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PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentation

https://github.com/showlab/sois

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Single-Stage Open-world Instance Segmentation with Cross-task Consistency Regularization

https://github.com/shqww/polarrcnn

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Polar R-CNN: End-to-End Lane Detection with Fewer Anchors

https://github.com/shreyasc-13/star

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Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation

https://github.com/shubhamagarwal12/warlearn

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WARLearn: Weather-Adaptive Representation Learning

https://github.com/shuhaolii/tits24lanelevel-traffic-benchmark

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Unifying Lane-Level Traffic Prediction from a Graph Structural Perspective: Benchmark and Baseline

https://github.com/shuishida/langprop

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LangProp: A code optimization framework using Large Language Models applied to driving

https://github.com/sibozhang/Depth-Guided-Inpainting

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DVI: Depth Guided Video Inpainting for Autonomous Driving

https://github.com/sijieaaa/hypliloc

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HypLiLoc: Towards Effective LiDAR Pose Regression with Hyperbolic Fusion

https://github.com/sijieaaa/prfusion

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PRFusion: Toward Effective and Robust Multi-Modal Place Recognition with Image and Point Cloud Fusion

https://github.com/sijieaaa/robustloc

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RobustLoc: Robust Camera Pose Regression in Challenging Driving Environments

https://github.com/simeonallmendinger/collafuse_imagen

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CollaFuse: Navigating Limited Resources and Privacy in Collaborative Generative AI

https://github.com/simondemoreau/led

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LED: Light Enhanced Depth Estimation at Night

https://github.com/simula-complex/deepqtest

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DeepQTest: Testing Autonomous Driving Systems with Reinforcement Learning and Real-world Weather Data

https://github.com/simula-complex/epitester

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EpiTESTER: Testing Autonomous Vehicles with Epigenetic Algorithm and Attention Mechanism

https://github.com/sinashish/mensa_mtda

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MEnsA: Mix-up Ensemble Average for Unsupervised Multi Target Domain Adaptation on 3D Point Clouds

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