https://github.com/western-oc2-lab/intrusion-detection-system-using-cnn-and-transfer-learning
공식 코드A Transfer Learning and Optimized CNN Based Intrusion Detection System for Internet of Vehicles
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/westlake-autolab/fusionad
공식 코드FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving
https://github.com/westny/dronalize
공식 코드Toward Unified Practices in Trajectory Prediction Research on Bird's-Eye-View Datasets
https://github.com/westny/mtp-go
공식 코드Evaluation of Differentially Constrained Motion Models for Graph-Based Trajectory Prediction
https://github.com/wgcban/spin_roadmapper
공식 코드https://github.com/wh200720041/SRLCD
공식 코드Online Visual Place Recognition via Saliency Re-identification
https://github.com/wh200720041/iscloam
공식 코드Intensity Scan Context: Coding Intensity and Geometry Relations for Loop Closure Detection
https://github.com/whuwangjr/sky-view-images
공식 코드Sky-GVIO: an enhanced GNSS/INS/Vision navigation with FCN-based sky-segmentation in urban canyon
https://github.com/wielgosz-info/carla-pedestrians
공식 코드https://github.com/willemeng/VLScene
공식 코드VLScene: Vision-Language Guidance Distillation for Camera-Based 3D Semantic Scene Completion
https://github.com/wingsweihua/colight
공식 코드CoLight: Learning Network-level Cooperation for Traffic Signal Control
https://github.com/wljungbergh/neuroncap
공식 코드NeuroNCAP: Photorealistic Closed-loop Safety Testing for Autonomous Driving
https://github.com/wmn7/universal_light
공식 코드UniTSA: A Universal Reinforcement Learning Framework for V2X Traffic Signal Control
https://github.com/wolfwjs/ganet
공식 코드A Keypoint-based Global Association Network for Lane Detection
https://github.com/wongkinyiu/yolov7
공식 코드YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/wongwaituck/attacking-optimization-layers-public
공식 코드Beyond NaN: Resiliency of Optimization Layers in The Face of Infeasibility
https://github.com/woodoxen/tactics2d
공식 코드Tactics2D: A Highly Modular and Extensible Simulator for Driving Decision-making
https://github.com/woodwindhu/dts
공식 코드Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection
https://github.com/woodwindhu/gsda
공식 코드Exploring the Devil in Graph Spectral Domain for 3D Point Cloud Attacks
https://github.com/woodwindhu/rangeldm
공식 코드https://github.com/woven-planet/l5kit
공식 코드CW-ERM: Improving Autonomous Driving Planning with Closed-loop Weighted Empirical Risk Minimization
https://github.com/woxihuanjiangguo/hydra-mdp
공식 코드Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation
https://github.com/woxihuanjiangguo/hydra-next
공식 코드Hydra-NeXt: Robust Closed-Loop Driving with Open-Loop Training
https://github.com/wqi/A2L
공식 코드https://github.com/wqi/WIMP
공식 코드https://github.com/wssun/badcode
공식 코드https://github.com/wu-cvgl/mba-slam
공식 코드MBA-SLAM: Motion Blur Aware Dense Visual SLAM with Radiance Fields Representation
https://github.com/wudongming97/prompt4driving
공식 코드https://github.com/wudongming97/topomlp
공식 코드TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoning
https://github.com/wuhanstudio/adversarial-camera
공식 코드A Human-in-the-Middle Attack against Object Detection Systems
https://github.com/wuhanstudio/adversarial-driving
공식 코드Adversarial Driving: Attacking End-to-End Autonomous Driving
https://github.com/wuhanstudio/whitebox-adversarial-toolbox
공식 코드A Human-in-the-Middle Attack against Object Detection Systems
https://github.com/wujingda/prioritized-human-in-the-loop-end-to-end-autonomous-driving
공식 코드Prioritized Experience-based Reinforcement Learning with Human Guidance for Autonomous Driving
https://github.com/wutad-wjy/charms
공식 코드CHARMS: A Cognitive Hierarchical Agent for Reasoning and Motion Stylization in Autonomous Driving
https://github.com/wuxiyang1996/iPLAN
공식 코드https://github.com/wuyuej/dhpm
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.