https://github.com/2023-MindSpore-1/ms-code-216/tree/main/r2plus1d
A Closer Look at Spatiotemporal Convolutions for Action Recognition
Papers with Code 아카이브
Action Localization
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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/2023-MindSpore-1/ms-code-217/tree/main/stgcn
DG-STGCN: Dynamic Spatial-Temporal Modeling for Skeleton-based Action Recognition
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/stnet
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tracktor
https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tracktor%2B%2B
https://github.com/2023-MindSpore-1/ms-code-24
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/2023-MindSpore-1/ms-code-35
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-1/ms-code-49
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-1/ms-code-68
A Closer Look at Spatiotemporal Convolutions for Action Recognition
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tracktor%2B%2B
https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tsn
https://github.com/2023-MindSpore-4/Code10/tree/main/VGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-4/Code10/tree/main/frustum-pointnet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-4/Code10/tree/main/glore_res
https://github.com/2023-MindSpore-4/Code6/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2023-MindSpore-4/Code7/tree/main/stnet
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition
https://github.com/2023-MindSpore-4/Code8/tree/main/AVA_cifar
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
https://github.com/2023-MindSpore-4/Code8/tree/main/BMN
BMN: Boundary-Matching Network for Temporal Action Proposal Generation
https://github.com/2023-MindSpore-4/Code8/tree/main/C3D
R-C3D: Region Convolutional 3D Network for Temporal Activity Detection
https://github.com/2023-MindSpore-4/Code9/tree/main/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2023-MindSpore-4/Code9/tree/main/VGG
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/2024-MindSpore-1/Code4/tree/main/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/2024-MindSpore-1/Code6/tree/main/BMN
BMN: Boundary-Matching Network for Temporal Action Proposal Generation
https://github.com/2024-MindSpore-1/Code9/tree/main/LOGO--Mindspore-master
FLAG3D: A 3D Fitness Activity Dataset with Language Instruction
https://github.com/2024-MindSpore-1/Code9/tree/main/gcn-c3d-mindspore-master
LOGO: A Long-Form Video Dataset for Group Action Quality Assessment
https://github.com/30Aniket/Graph-Convolutional-Networks-GCNs
Semi-Supervised Classification with Graph Convolutional Networks
https://github.com/404nofound/gat
https://github.com/4pygmalion/GAT_tensorflow
https://github.com/812618101/TAL-Demo
Deep Concept-wise Temporal Convolutional Networks for Action Localization
https://github.com/AD2605/Action-Recognition
A Closer Look at Spatiotemporal Convolutions for Action Recognition
https://github.com/AI-Guru/pointcloud_experiments
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/AIOSYM/dl-model-gallery
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/AbdalaDiasse/Video-classification-for-oil-quality-estimation
https://github.com/AbdurrahmanNadi/activity_recognition_web_service
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/AbertayMachineLearningGroup/machine-learning-SIEM-water-infrastructure
Improving SIEM for Critical SCADA Water Infrastructures Using Machine Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.