https://github.com/Fragjacker/Pointcloud-grad-CAM
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Papers with Code 아카이브
Action Localization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 4
- 평가표
- 0
- 보존된 평가 기록
- 0
Action Localization is finding the spatial and temporal co ordinates for an action in a video. An action localization model will identify which frame an action start and ends in video and return the x,y coordinates of an action. Further the co ordinates will change when the object performing action undergoes a displacement.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/FrederikSchorr/sign-language
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/FunmiKesa/JLA
Joint Learning Architecture for Multiple Object Tracking and Trajectory Forecasting
https://github.com/GOD-GOD-Autonomous-Vehicle/self-pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/GabrieleMonte/CoMBInE
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Gbouna/Action-Recognition-for-Privacy-Preserving-Ambient-Assisted-Living
https://github.com/Gbouna/HT-ConvNet
https://github.com/GeyuanZhang/st-gcn-master
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/Godot-yry/VGG16_mindspore
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Gojay001/toolkit-DeepLearning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/GraphSAINT/GraphSAINT
https://github.com/HamzaGbada/GCN-Numpy
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/HaoyuJi/TRG-Net
Text-Derived Relational Graph-Enhanced Network for Skeleton-Based Action Segmentation
https://github.com/HarmanDotpy/Normalizations-in-Deep-Learning
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Harry-Muzart/harry-muzart.github.io
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/Harut0726/my-pointnet-tensorflow
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/HazyResearch/hgcn
https://github.com/HeapHop30/graph-attention-nets
https://github.com/HoganZhang/BSN-boundary-sensitive-network.pytorch
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
https://github.com/HoganZhang/mot_neural_solver
https://github.com/HoganZhang/pygcn_python3
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/HoganZhang/weakly-action-localization
Weakly Supervised Action Localization by Sparse Temporal Pooling Network
https://github.com/HollrayChan/gradcam-plus-plus
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
https://github.com/HuCui2022/JPFormer
https://github.com/IMvision12/keras-vision-models
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/ISICV/ManTraNet
https://github.com/IllinoisGraphBenchmark/IGB-Datasets
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/InfoX-SEU/DAE-AQA
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment
https://github.com/InfoX-SEU/DAE_AQA
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment
https://github.com/InwoongLee/TS-LSTM
https://github.com/JJBOY/BMN-Boundary-Matching-Network
BMN: Boundary-Matching Network for Temporal Action Proposal Generation
https://github.com/Jacoo-Zhao/3D-Pose-Based-Feedback-For-Physical-Exercises
Learning Trajectory Dependencies for Human Motion Prediction
https://github.com/Jagyan/ghost_radarpoint_detection
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/Javed002/Object_detection_PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/JeansonYang/VGG16-MindSpore
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/JeffCHEN2017/WSSTG
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.