https://github.com/ChenhongyiYang/SG-NMS
공식 코드Learning to Separate: Detecting Heavily-Occluded Objects in Urban Scenes
Papers with Code 아카이브
Autonomous Vehicles
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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/Chenzhaowei13/Light-Condition-Style-Transfer
공식 코드https://github.com/ChongjianGE/MetaBEV
공식 코드MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation
https://github.com/ChuchuHan/DMRNet
공식 코드https://github.com/CnnDepth/MAOMaps
공식 코드MAOMaps: A Photo-Realistic Benchmark For vSLAM and Map Merging Quality Assessment
https://github.com/CnnDepth/tx2_fcnn_node
공식 코드Real-time Vision-based Depth Reconstruction with NVidia Jetson
https://github.com/CongliangLi/LabelImg3D
공식 코드https://github.com/CongliangLi/SMOPE-Net
공식 코드https://github.com/Coolshanlan/DDFH-active-3Ddet
공식 코드Distribution Discrepancy and Feature Heterogeneity for Active 3D Object Detection
https://github.com/DaRL-LibSignal/LibSignal
공식 코드https://github.com/Danial-Qashqai/CSFNet
공식 코드https://github.com/Daniel-Liu-c0deb0t/Adversarial-point-perturbations-on-3D-objects
공식 코드https://github.com/Daniel-xsy/RoboBEV
공식 코드Benchmarking and Improving Bird's Eye View Perception Robustness in Autonomous Driving
https://github.com/DanielCoelho112/priboot
공식 코드PRIBOOT: A New Data-Driven Expert for Improved Driving Simulations
https://github.com/DapengFeng/cartgs
공식 코드CaRtGS: Computational Alignment for Real-Time Gaussian Splatting SLAM
https://github.com/Das-Boot/bot_or_not
공식 코드https://github.com/DavidWanke/PyAutoDriveRL
공식 코드https://github.com/DenisTome/DeepPed
공식 코드https://github.com/Dependable-Intelligent-Systems-Lab/xwhy/tree/main/examples/Point%20Cloud%20Examples
공식 코드https://github.com/DependableSystemsLab/TensorFI
공식 코드TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications
https://github.com/Depth2World/VLADBench
공식 코드Fine-Grained Evaluation of Large Vision-Language Models in Autonomous Driving
https://github.com/Derekabc/MARL_CAVs
공식 코드Deep Multi-agent Reinforcement Learning for Highway On-Ramp Merging in Mixed Traffic
https://github.com/DerrickXuNu/v2x-vit
공식 코드V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer
https://github.com/DexterJZ/eval_driving_safety
공식 코드Evaluating Adversarial Attacks on Driving Safety in Vision-Based Autonomous Vehicles
https://github.com/DeyvidKochanov-TomTom/kprnet
공식 코드KPRNet: Improving projection-based LiDAR semantic segmentation
https://github.com/DingJianhao/stable-snn
공식 코드https://github.com/Dingyuan-Zheng/maskPS
공식 코드https://github.com/Div99/W-Stereo-Disp
공식 코드https://github.com/DrMahdiRezaei/DeepSOCIAL
공식 코드DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic
https://github.com/DriveVLA/OpenDriveVLA
공식 코드OpenDriveVLA: Towards End-to-end Autonomous Driving with Large Vision Language Action Model
https://github.com/E2E-AD/AD-MLP
공식 코드Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes
https://github.com/EGiunchiglia/ROAD-R
공식 코드ROAD-R: The Autonomous Driving Dataset with Logical Requirements
https://github.com/ENSTA-U2IS-AI/Multimodal_Deep_segmentation
공식 코드InfraParis: A multi-modal and multi-task autonomous driving dataset
https://github.com/ENSTA-U2IS-AI/torch-uncertainty
공식 코드https://github.com/EdAlexAguilar/reward_shaping
공식 코드Hierarchical Potential-based Reward Shaping from Task Specifications
https://github.com/EladSharony/miso
공식 코드Learning Multiple Initial Solutions to Optimization Problems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.