videodnn Goto Github PK
Type: Organization
Bio: for deep learning in video/media
Location: Chaoyang District, Peking, P.R.China
Type: Organization
Bio: for deep learning in video/media
Location: Chaoyang District, Peking, P.R.China
3D Dense Connected Convolutional Network (3D-DenseNet for action recognition)
3D ResNets for Action Recognition (CVPR 2018)
Action recognition using soft attention based deep recurrent neural networks
Explore Action Recognition
Diagnostic tools and additional visualizations from "What Actions are Needed for Understanding Human Actions in Videos?" ICCV 2017
A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.
automatic video description generation with GPU training
Code/Model release for NIPS 2017 paper "Attentional Pooling for Action Recognition"
A curated list of action recognition and related area resources
The official Codes for NeurIPS 2019 paper. Quanfu Fan, Ricarhd Chen, Hilde Kuehne, Marco Pistoia, David Cox, "More Is Less: Learning Efficient Video Representations by Temporal Aggregation Modules"
train C3D with keras for action recognition
C3D for Keras + TensorFlow
C3D is a modified version of BVLC tensorflow to support 3D ConvNets.
Activity Recognition Algorithms for the Charades Dataset
Learning Video Representations from Correspondence Proposals (CVPR 2019 Oral)
Activity Recognition in Videos using UCF101 dataset
Deep human action recognition and pose estimation
API of DouYin for Humans used to Crawl Popular Videos and Musics
Python bindings for FFmpeg - with complex filtering support
Code that accompanies my blog post outlining five video classification methods in Keras and TensorFlow
Google AI Research
GPU based optical flow extraction in OpenCV
HACS: Human Action Clips and Segments Dataset
Keras implementation of Human Action Recognition for the data set State Farm Distracted Driver Detection (Kaggle)
TensorFlow code for finetuning I3D model on UCF101.
GitHub repository for "Improving Video Generation for Multi-functional Applications"
Convolutional neural network model for video classification trained on the Kinetics dataset.
Learning Spatio-Temporal Representation with Local and Global Diffusion
MMGCN: Multi-modal Graph Convolution Network forPersonalized Recommendation of Micro-video
The pretrained models trained on Moments in Time Dataset
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Open source projects and samples from Microsoft.
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Data-Driven Documents codes.
China tencent open source team.