TensorFlow implementation for "Guided Optical Flow Learning"
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Updated
Jun 9, 2017 - Python
TensorFlow implementation for "Guided Optical Flow Learning"
Computer Vision: African Motion Content Network
Caffe implementation for "Hidden Two-Stream Convolutional Networks for Action Recognition"
Temporal 3D ConvNet
Support LRCN(both rgb and optical-flow). This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors
Implemented Kernel SVM using Quadratic Programming and Stochastic Gradient Descent
Action Recognition using Convolutional Neural Network (CNN)
Pytorch inception v4 for human actions recognition.
Use 3D ResNet to extract features of UCF101 and HMDB51 and then classify them.
Using two stream architecture to implement a classic action recognition method on UCF101 dataset
Implementation Code of the paper Optical Flow Guided Feature, CVPR 2018
PyTorch implementation for "Gated Transfer Network for Transfer Learning"
A pytorch implementation of a text to videos GAN
Using two stream architecture to implement a classic action recognition method on UCF101 dataset
STEP: Spatio-Temporal Progressive Learning for Video Action Detection. CVPR'19 (Oral)
Computer Vision Project : Action Recognition on UCF101 Dataset
Simple Action Recognition experimentation with the UCF101 Dataset and EfficientNets.
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