## <font face="楷体">说明</font>
**动作识别(Action Recognition)任务中常见的模型Pytorch实现**
## <font face="楷体">主要模型</font>
**3D卷积类**
- **C3D**:[Learning Spatiotemporal Features with 3D Convolutional Networks](https://arxiv.org/pdf/1412.0767.pdf) -*D.Tran et al, ICCV 2015*.
- **I3D**:[Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset](https://arxiv.org/pdf/1705.07750.pdf) -*J.Carreira et al, CVPR 2017*.
- **P3D**:[Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks](https://arxiv.org/pdf/1711.10305.pdf) -*Z.Qui et al, ICCV 2017*.
- **R(2+1)D**:[A Closer Look at Spatiotemporal Convolutions for Action Recognition](https://arxiv.org/pdf/1711.11248.pdf) -*D.Tran et al, CVPR 2018*.
- **3D ResNets**:[Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?](https://arxiv.org/pdf/1711.09577.pdf) -*K.Hara et al, CVPR 2019*.
**Two Stream类**
- **Two Stream**:[Two-Stream Convolutional Networks for Action Recognition in Videos](https://papers.nips.cc/paper/5353-two-stream-convolutional-networks-for-action-recognition-in-videos.pdf) -*K.Simonyan and A.Zisserman, NIPS 2014*.
- **Two Stream Fused**:[Convolutional Two-Stream Network Fusion for Video Action Recognition](https://arxiv.org/pdf/1604.06573.pdf) -*C.Feichtenhofer et al, CVPR 2016*.
- **TSN**:[Temporal Segment Networks: Towards Good Practices for Deep Action Recognition](https://arxiv.org/pdf/1608.00859.pdf) -*L.Wang et al, arXiv 2016*
**CNN+RNN类**
- **LRCN**:[Long-term Recurrent Convolutional Networks for Visual Recognition and Description](https://arxiv.org/pdf/1411.4389.pdf) -*J.Donahue et al, CVPR 2015*.
- **ConvLSTM**:[Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting](https://arxiv.org/pdf/1506.04214.pdf) -*X Shi et al, NIPS 2015*.
## <font face="楷体">参考</font>
- R(2+1)D: https://github.com/irhum/R2Plus1D-PyTorch
- 多种模型实现: https://github.com/MRzzm/action-recognition-models-pytorch
- R(2+1)D: https://github.com/kenshohara/3D-ResNets-PyTorch
- C3D: https://github.com/jfzhang95/pytorch-video-recognition
- HOG:https://www.analyticsvidhya.com/blog/2019/09/feature-engineering-images-introduction-hog-feature-descriptor/
- HOF:https://blog.csdn.net/wsp_1138886114/article/details/84400392
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读书笔记:动作识别(Action Recognition)常见模型的Pytorch实现.zip (63个子文件)
读书笔记:动作识别(Action Recognition)常见模型的Pytorch实现
Action-Recognition-Learning
CNN+RNN
ConvLSTM
model.py 7KB
README.md 202B
README.md 206B
LRCN
model-useLSTMCell.py 3KB
README.md 195B
model-useBiLSTM.py 2KB
3D-CNN
P3D
model.py 7KB
README.md 193B
C3D
model.py 3KB
README.md 242B
I3D
model.py 4KB
README.md 287B
README.md 382B
R2+1D
model.py 10KB
README.md 299B
Feature-Extract
HOF.py 2KB
HOG.py 2KB
imgs
tst2.jpg 13KB
output.avi 5.73MB
umbrella.jpg 93KB
pedestrian.mp4 1.59MB
tst3.jpg 28KB
tst1.jpg 14KB
README.md 108B
SIFT.py 874B
.git
index 5KB
HEAD 23B
refs
heads
master 41B
tags
remotes
origin
master 41B
objects
pack
pack-080feb785227a214ca5d4d4eb9c399e62e263c9d.idx 3KB
pack-080feb785227a214ca5d4d4eb9c399e62e263c9d.pack 8.95MB
info
FETCH_HEAD 136B
logs
HEAD 130B
refs
heads
master 130B
remotes
origin
master 144B
hooks
config 273B
branches
Two-Stream
README.md 350B
images
experiment-2.jpg 77KB
R2+1D-2.jpg 140KB
P3D.jpg 86KB
ConvLSTM.jpg 63KB
TSN.jpg 173KB
I3D-2.jpg 134KB
C3D.jpg 93KB
I3D-1.jpg 105KB
two-stream-fused-1.jpg 77KB
experiment-1.jpg 71KB
two-stream-fused-2.jpg 173KB
R2+1D-1.jpg 184KB
two-stream.jpg 172KB
LRCN.jpg 184KB
Experiments
UCF-datasets
README.md 931B
C3D
mypath.py 784B
dataset.py 10KB
model.py 2KB
inference.py 2KB
C3D_model.py 5KB
dataset_labels
ucf_labels.txt 1KB
pretrained
README.md 196B
run
run_0
models
Sep23_11-50-38
events.out.tfevents.1600833038.cdl-dev-4-10-128-2-137 14KB
train.py 8KB
README.md 69B
README.md 2KB
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