https://github.com/pminhtam/2D-3D_Multitask_Deep_Learning
2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning
Papers with Code 아카이브
Action Recognition In Videos
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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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/pwc-1/Paper-9/tree/main/3/vat
VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text
https://github.com/rajskar/CS763Project
RED: Reinforced Encoder-Decoder Networks for Action Anticipation
https://github.com/rijuldhir/TSM
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/rlaengud123/CMC_LRCN
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
https://github.com/ryanchesler/comma-speed-challenge
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
https://github.com/santhoshpkumar/Hand-gesture-recognition-using-neural-networks
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/scouTT1/C3D
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/sunutf/TSM
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/taufikxu/youtube
https://github.com/thaitruongan/camera-surveillance-ai
https://github.com/tianfr/mononerf
https://github.com/tianfr/semantic-flow
https://github.com/titu1994/tf_star_rnn
https://github.com/tomar840/two-stream-fusion-for-action-recognition-in-videos
Convolutional Two-Stream Network Fusion for Video Action Recognition
https://github.com/towhee-io/towhee
https://github.com/wangxiang1230/SSTAP
https://github.com/waynshang/Gesture-Recognition-with-3DCNN
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/woodfrog/ActionRecognition
Two-Stream Convolutional Networks for Action Recognition in Videos
https://github.com/wushidonguc/two-stream-action-recognition-keras
UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
https://github.com/xingyul/meteornet
Learning Video Representations from Correspondence Proposals
https://github.com/xiuyu0000/vision/blob/main/mindvision/msvideo/models/c3d.py
Learning Spatiotemporal Features with 3D Convolutional Networks
https://github.com/youngjun0627/movie-rating
https://github.com/zhoubolei/TRN-pytorch
https://github.com/zwtu/YOWO-Paddle
You Only Watch Once: A Unified CNN Architecture for Real-Time Spatiotemporal Action Localization
https://gitlab.com/birder/birder
Hiera: A Hierarchical Vision Transformer without the Bells-and-Whistles
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.