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/scope-lab-vu/anti-carla

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ANTI-CARLA: An Adversarial Testing Framework for Autonomous Vehicles in CARLA

https://github.com/sdqesdataset/sdqes_generation

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Streaming Detection of Queried Event Start

https://github.com/sdret/a-solution-to-co-occurence-bias-in-pedestrian-attribute-recognition

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A Solution to Co-occurrence Bias: Attributes Disentanglement via Mutual Information Minimization for Pedestrian Attribute Recognition

https://github.com/sdret/pedestrian-attribute-recognition-as-label-balanced-multi-label-learning

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Pedestrian Attribute Recognition as Label-balanced Multi-label Learning

https://github.com/seawee1/driver-dojo

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

https://github.com/sel118/LaneAF

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LaneAF: Robust Multi-Lane Detection with Affinity Fields

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/adnet

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ADNet: Lane Shape Prediction via Anchor Decomposition

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/shacharp/Adaptive-LiDAR-Sampling

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Adaptive LiDAR Sampling and Depth Completion using Ensemble Variance

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/shahram95/superpointslam3

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SuperPoint-SLAM3: Augmenting ORB-SLAM3 with Deep Features, Adaptive NMS, and Learning-Based Loop Closure

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/shangtse/robust-physical-attack

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ShapeShifter: Robust Physical Adversarial Attack on Faster R-CNN Object Detector

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/sharmasushil/navigating-uncertainty-trajectory-prediction

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Navigating Uncertainty: The Role of Short-Term Trajectory Prediction in Autonomous Vehicle Safety

https://github.com/shashankskagnihotri/benchmarking_robustness

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DispBench: Benchmarking Disparity Estimation to Synthetic Corruptions

https://github.com/shaswata09/offroad-path-planning

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URA*: Uncertainty-aware Path Planning using Image-based Aerial-to-Ground Traversability Estimation for Off-road Environments

https://github.com/shawlen/dtignn

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Modeling Network-level Traffic Flow Transitions on Sparse Data

https://github.com/shengchao-y/maaac-driving

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Agent-Agnostic Centralized Training for Decentralized Multi-Agent Cooperative Driving

https://github.com/shenqildr/ScorNet

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A Robust and Reliable Point Cloud Recognition Network Under Rigid Transformation

https://github.com/shenyanqing1105/ForestLPR-CVPR2025

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ForestLPR: LiDAR Place Recognition in Forests Attentioning Multiple BEV Density Images

https://github.com/sherrychen1120/MIDAS

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MIDAS: Multi-agent Interaction-aware Decision-making with Adaptive Strategies for Urban Autonomous Navigation

https://github.com/sherwinbahmani/ynet_adaptive

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Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective

https://github.com/shichaoy/cube_slam

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CubeSLAM: Monocular 3D Object SLAM

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