date: 2019-08-26 09:44:22
tags: 
- CNN 
- CNN3D
- DNN
- Video Representation
- Action Recognition
- Video Classification
- Spatiotemporal 

3D-CNN Method

iDT
LRCN		CVPR 2015
LSTM composite model
C3D		2015
TSN		ECCV 2016
R3DCNN	NVIDIA	2016
P3D	MSRA	ICCV 2017
R3D/2.5D		2017
T3D		2017
R2+1D		2018

--

---

General LIb:

[ video model zoo (caffe2) ] https://github.com/facebookresearch/VMZ

Currently, this codebase supports the following models:

• R(2+1)D, MCx models [1].
• CSN models [2].
• R(2+1)D and CSN models pre-trained on large-scale (65 million!) weakly-supervised public Instagram videos (IG-65M) [3].

C3D

[github caffe ]https://github.com/facebook/C3D

[ github tensorflow ]https://github.com/hx173149/C3D-tensorflow

[github pytorch] https://github.com/jfzhang95/pytorch-video-recognition

3x3x3 Kernel

P3D

[ caffe ] https://github.com/ZhaofanQiu/pseudo-3d-residual-networks

[ pytorch ] https://github.com/jfzhang95/pytorch-video-recognition

Learning spatio-temporal representation with pseudo-3d residual networks. In ICCV, 2017.

T3D*

Architecture: DenseNet + 3D

[ github pytorch] https://github.com/MohsenFayyaz89/T3D

Res3D/R3D

architecture: ResNet + 3DConv

[github pytorch] https://github.com/jfzhang95/pytorch-video-recognition

R2.5D

R2+1D

[ offical video model zoo (caffe2) ] https://github.com/facebookresearch/VMZ

[ github PyTorch] https://github.com/leftthomas/R2Plus1D-C3D

R3DCNN

[NVIDIA]https://research.nvidia.com/sites/default/files/publications/NVIDIA_R3DCNN_cvpr2016.pdf

[tensorflow ]https://github.com/breadbread1984/R3DCNN

[tensorflow ] https://github.com/kilsenp/R3DCNN-tensorflow

architecture: C3D + RNN

TSN

[github caffe ] https://github.com/yjxiong/temporal-segment-networks

[ caffe opensource ] https://github.com/yjxiong/caffe

[Paper] https://arxiv.org/pdf/1608.00859.pdf

I3D

Architecture: Inception base

[git keras ] https://github.com/OanaIgnat/i3d_keras

[Paper ] https://arxiv.org/pdf/1705.07750.pdf