https://github.com/CrazySherman/goodlife
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
Papers with Code 아카이브
Action Recognition In Videos
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Action Recognition in Videos is a task in computer vision and pattern recognition where the goal is to identify and categorize human actions performed in a video sequence. The task involves analyzing the spatiotemporal dynamics of the actions and mapping them to a predefined set of action classes, such as running, jumping, or swimming.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ElricXin/Skeleton-MixFormer
https://github.com/HardyYoungX/C3D
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/HsinYingLee/OPN
Two-Stream Convolutional Networks for Action Recognition in Videos
https://github.com/KiUngSong/Vision
https://github.com/LukasHedegaard/co3d
https://github.com/MIT-HAN-LAB/temporal-shift-module
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/MarkoLewis-Projects/Sign_language_detection
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/Maxchengqin/DSCNet
https://github.com/MekkaSiekka/C3D-UCF11-Tensorflow
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/Michaelgod/test
Two-Stream Convolutional Networks for Action Recognition in Videos
https://github.com/MichiganCOG/M-PACT
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/Mind23-2/MindCode-88/tree/main/slowfast
https://github.com/MindCode-4/code-13/tree/main/vat
VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text
https://github.com/MindCode-4/code-3/tree/main/florence2
https://github.com/MindCode-4/code-9/tree/main/vat
VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text
https://github.com/MindSpore-paper-code-2/code3/tree/main/trn
https://github.com/MindSpore-paper-code-2/code3/tree/main/tsn
https://github.com/MindSpore-paper-code-3/code6/tree/main/C3D
R-C3D: Region Convolutional 3D Network for Temporal Activity Detection
https://github.com/MindSpore-scientific-2/code-3/tree/main/temporal-and-aspectual-entailment
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/MindSpore-scientific/code-1/tree/main/Simba
Simba: Mamba augmented U-ShiftGCN for Skeletal Action Recognition in Videos
https://github.com/MindSpore-scientific/code-10/tree/main/Simba
Simba: Mamba augmented U-ShiftGCN for Skeletal Action Recognition in Videos
https://github.com/MindSpore-scientific/code-14/tree/main/temporal-and-aspectual-entailment
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/MindSpore-scientific/code-2/tree/main/temporal-and-aspectual-entailment
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/Nortinwell/TSN
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/pp-tsn.md
https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/zh-CN/model_zoo/recognition/slowfast.md
https://github.com/ParitoshParmar/HalluciNet--PyTorch
HalluciNet-ing Spatiotemporal Representations Using a 2D-CNN
https://github.com/Stepphonwol/my_yowo
You Only Watch Once: A Unified CNN Architecture for Real-Time Spatiotemporal Action Localization
https://github.com/VEDANTGHODKE/Hand-Gesture-Recognition-Using-Neural-Networks
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/VinnyCSY/BHaRNet
https://github.com/WavesUR/embedded_TSM
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/XuHao9166/TSN_BehaviorRecognition_ForwardCalculation
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/XuHao9166/TSN_BehaviorRecognition_GenerateTrainImages
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/Ysp9714/SlowFastNet-keras
https://github.com/ZJCV/Non-local
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.