https://github.com/MindSpore-paper-code-3/code10/tree/main/flownet2
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
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/MindSpore-paper-code-3/code4/tree/main/flownet2
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
https://github.com/MindSpore-paper-code-3/code5/tree/main/ReIDStrongBaseline
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/MindSpore-paper-code-3/code6/tree/main/AVA_cifar
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
https://github.com/MindSpore-paper-code-3/code6/tree/main/BMN
BMN: Boundary-Matching Network for Temporal Action Proposal Generation
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-paper-code-3/code7/tree/main/flownet2
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
https://github.com/MindSpore-paper-code-3/code8/tree/main/dpn
https://github.com/MindSpore-paper-code-3/code9/tree/main/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/MindSpore-paper-code-3/code9/tree/main/PointNet2
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/MindSpore-scientific-2/code-12/tree/main/LGL-INR-master
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-2/code-4/tree/main/GR-HSTU
https://github.com/MindSpore-scientific-2/code-8/tree/main/pytorch_convgru
Delving Deeper into Convolutional Networks for Learning Video Representations
https://github.com/MindSpore-scientific-2/code-8/tree/main/temporal-normalizing-flows
Contextualized Spatio-Temporal Contrastive Learning with Self-Supervision
https://github.com/MindSpore-scientific/code-11/tree/main/pytorch_convgru
ConvGRU in Fine-grained Pitching Action Recognition for Action Outcome Prediction
https://github.com/MindSpore-scientific/code-12/tree/main/AVA_hpa
1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020
https://github.com/MindSpore-scientific/code-13/tree/main/pytorch_convgru
ConvGRU in Fine-grained Pitching Action Recognition for Action Outcome Prediction
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/MindSpore-scientific/code-3/tree/main/ACGNet
ACGNet: Action Complement Graph Network for Weakly-supervised Temporal Action Localization
https://github.com/MisaOgura/flashtorch
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/MkuuWaUjinga/Self-Supervised-Learning-for-Tracktor
https://github.com/ModelBunker/PointNet-TensorFlow
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/Moon-Xuezha/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
https://github.com/MrRiahi/Convolutional-Neural-Networks-Tensorflow
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/MrSyee/rnn_autoenc
https://github.com/NASA-NeMO-Net/NeMO-Net
Very Deep Convolutional Networks for Large-Scale Image Recognition
https://github.com/NVIDIA/flownet2-pytorch
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
https://github.com/Negus25/GAT-Mindspore
https://github.com/Nortinwell/TSN
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
https://github.com/OanaIgnat/i3d_keras
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/Ontheway361/BSN_pytorch
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
https://github.com/OpenXAIProject/LRP_for_LSTM_Korean_dataset
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition
https://github.com/PPPrior/i3d-pytorch
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset
https://github.com/PaParaZz1/PointNet
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.