ucf101

Tutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101

Using two stream architecture to implement a classic action recognition method on UCF101 dataset

This repository host the code for real-time action detection paper

STEP: Spatio-Temporal Progressive Learning for Video Action Detection. CVPR'19 (Oral)

Video Platform for Action Recognition and Object Detection in Pytorch

Implementation Code of the paper Optical Flow Guided Feature, CVPR 2018

Caffe implementation for "Hidden Two-Stream Convolutional Networks for Action Recognition"

Video Recognition using Mixed Convolutional Tube (MiCT) on PyTorch with a ResNet backbone

My experimentation around action recognition in videos. Contains Keras implementation for C3D network based on original paper "Learning Spatiotemporal Features with 3D Convolutional Networks", Tran et al. and it includes video processing pipelines coded using mPyPl package. Model is being benchmarked on popular UCF101 dataset and achieves results similar to those reported by authors

Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.

Use 3D ResNet to extract features of UCF101 and HMDB51 and then classify them.

Computer Vision Project : Action Recognition on UCF101 Dataset

[CVPR 2022] End-to-End Semi-Supervised Learning for Video Action Detection

Action recognition tutorial using UCF-101 dataset.

[AAAI 2023 (Oral)] CrissCross: Self-Supervised Audio-Visual Representation Learning with Relaxed Cross-Modal Synchronicity

TensorFlow implementation for "Guided Optical Flow Learning"

Implementation of LTC-SUM: Lightweight Client-driven Personalized Video Summarization Framework Using 2D CNN

Implemented a CNN-LSTM Action Recognizer for dynamic motion analysis, integrating convolutional and recurrent neural networks to efficiently recognize and classify actions in video data of UCF101 dataset.

由视频数据集生成optical flow，frames，warped flow