https://github.com/gymoon10/Instance-Segmentation-with-SpatialEmbedding-CA
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
Papers with Code 아카이브
Autonomous Vehicles
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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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/gywns6287/baam
https://github.com/haithink/myWindowsDarknet
https://github.com/haiyang-w/dsvt
UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation
https://github.com/haiyang-w/git
UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation
https://github.com/halajun/vdo_slam
https://github.com/halimasoulb/human-pose-estimation-3d-lidar
https://github.com/hamidmousavi0/reliable-relu-toolbox
https://github.com/hamidriasat/DDRNets
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
https://github.com/hamzaMahdi/darknet
https://github.com/hanghang177/pedestrian_awareness
https://github.com/hanhanAnderson/LSF-SAC
https://github.com/hankpark0706/darknet
https://github.com/haomo-ai/OverlapTransformer
https://github.com/haonanguo/remote-sensing-chatgpt
https://github.com/haosulab/ManiSkill-Learn
https://github.com/harryhan618/LaneNet
Semantic Instance Segmentation with a Discriminative Loss Function
https://github.com/harryhan618/SCNN_Pytorch
Spatial As Deep: Spatial CNN for Traffic Scene Understanding
https://github.com/harryhan618/scnn
Spatial As Deep: Spatial CNN for Traffic Scene Understanding
https://github.com/harsh2011/Yolov3-Detector
https://github.com/harshayugirase/human-path-prediction
It Is Not the Journey but the Destination: Endpoint Conditioned Trajectory Prediction
https://github.com/harvard-edge/source-seeking
https://github.com/hasanirtiza/PedesFormer-SwinTransformer-For-Pedestrian-Detection
Pedestrian Detection: Domain Generalization, CNNs, Transformers and Beyond
https://github.com/hbzhang/AwesomeSelfDriving
Reinforcement Learning and Deep Learning based Lateral Control for Autonomous Driving
https://github.com/heechul/picar
https://github.com/heiner/scalable_agent
https://github.com/hejiawei2023/ug3dmot
Probabilistic 3D Multi-Object Tracking for Autonomous Driving
https://github.com/hellotrik/torch_yolov3
https://github.com/henry1iu/tnt-trajectory-prediction
VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation
https://github.com/henry1iu/tnt-trajectory-predition
https://github.com/henrytsui000/YOLO
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
https://github.com/hershd23/ObjectLocalizer
https://github.com/heshameraqi/Dynamic-CIL-Driving
Dynamic Conditional Imitation Learning for Autonomous Driving
https://github.com/hhuaibo/darknet
https://github.com/hirohiro23/Darknet
https://github.com/hisfog/SfMNeXt-Impl
SQLdepth: Generalizable Self-Supervised Fine-Structured Monocular Depth Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.