Keras Kinetics I3dkeras implementation of inflated 3d from Quo Vardis paper + weights
Stars: ✭ 116 (-46.54%)
Tdn[CVPR 2021] TDN: Temporal Difference Networks for Efficient Action Recognition
Stars: ✭ 72 (-66.82%)
MmactionAn open-source toolbox for action understanding based on PyTorch
Stars: ✭ 1,711 (+688.48%)
Dd NetA lightweight network for body/hand action recognition
Stars: ✭ 161 (-25.81%)
Video ClassificationTutorial for video classification/ action recognition using 3D CNN/ CNN+RNN on UCF101
Stars: ✭ 543 (+150.23%)
3d Resnets3D ResNets for Action Recognition
Stars: ✭ 95 (-56.22%)
HakeHAKE: Human Activity Knowledge Engine (CVPR'18/19/20, NeurIPS'20)
Stars: ✭ 132 (-39.17%)
C3d KerasC3D for Keras + TensorFlow
Stars: ✭ 171 (-21.2%)
Tsn PytorchTemporal Segment Networks (TSN) in PyTorch
Stars: ✭ 895 (+312.44%)
Hidden Two StreamCaffe implementation for "Hidden Two-Stream Convolutional Networks for Action Recognition"
Stars: ✭ 179 (-17.51%)
Mmaction2OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
Stars: ✭ 684 (+215.21%)
Movienet ToolsTools for movie and video research
Stars: ✭ 113 (-47.93%)
Two Stream PytorchPyTorch implementation of two-stream networks for video action recognition
Stars: ✭ 428 (+97.24%)
UntrimmednetWeakly Supervised Action Recognition and Detection
Stars: ✭ 152 (-29.95%)
Vidvrd HelperTo keep updates with VRU Grand Challenge, please use https://github.com/NExTplusplus/VidVRD-helper
Stars: ✭ 81 (-62.67%)
3d Resnets Pytorch3D ResNets for Action Recognition (CVPR 2018)
Stars: ✭ 3,169 (+1360.37%)
DapsThis repo allocate DAPs code of our ECCV 2016 publication
Stars: ✭ 74 (-65.9%)
Video CaffeVideo-friendly caffe -- comes with the most recent version of Caffe (as of Jan 2019), a video reader, 3D(ND) pooling layer, and an example training script for C3D network and UCF-101 data
Stars: ✭ 172 (-20.74%)
Hake ActionAs a part of the HAKE project, includes the reproduced SOTA models and the corresponding HAKE-enhanced versions (CVPR2020).
Stars: ✭ 72 (-66.82%)
Action RecognitionExploration of different solutions to action recognition in video, using neural networks implemented in PyTorch.
Stars: ✭ 129 (-40.55%)
Fight detectionReal time Fight Detection Based on 2D Pose Estimation and RNN Action Recognition
Stars: ✭ 65 (-70.05%)
AmassData preparation and loader for AMASS
Stars: ✭ 180 (-17.05%)
Resgcnv1ResGCN: an efficient baseline for skeleton-based human action recognition.
Stars: ✭ 50 (-76.96%)
I3d finetuneTensorFlow code for finetuning I3D model on UCF101.
Stars: ✭ 128 (-41.01%)
Okutama ActionOkutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection
Stars: ✭ 36 (-83.41%)
Hcn Prototypeloss PytorchHierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)
Stars: ✭ 17 (-92.17%)
MmskeletonA OpenMMLAB toolbox for human pose estimation, skeleton-based action recognition, and action synthesis.
Stars: ✭ 2,378 (+995.85%)
Two Stream Action RecognitionUsing two stream architecture to implement a classic action recognition method on UCF101 dataset
Stars: ✭ 705 (+224.88%)
ModelfeastPytorch model zoo for human, include all kinds of 2D CNN, 3D CNN, and CRNN
Stars: ✭ 116 (-46.54%)
TimeceptionTimeception for Complex Action Recognition, CVPR 2019 (Oral Presentation)
Stars: ✭ 153 (-29.49%)
Gluon CvGluon CV Toolkit
Stars: ✭ 5,001 (+2204.61%)
TddTrajectory-pooled Deep-Convolutional Descriptors
Stars: ✭ 99 (-54.38%)
Realtime Action RecognitionApply ML to the skeletons from OpenPose; 9 actions; multiple people. (WARNING: I'm sorry that this is only good for course demo, not for real world applications !!! Those ary very difficult !!!)
Stars: ✭ 417 (+92.17%)
VipVideo Platform for Action Recognition and Object Detection in Pytorch
Stars: ✭ 175 (-19.35%)
Video Dataset Loading PytorchGeneric PyTorch Dataset Implementation for Loading, Preprocessing and Augmenting Video Datasets
Stars: ✭ 92 (-57.6%)
StepSTEP: Spatio-Temporal Progressive Learning for Video Action Detection. CVPR'19 (Oral)
Stars: ✭ 196 (-9.68%)
Hand pose actionDataset and code for the paper "First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotations", CVPR 2018.
Stars: ✭ 173 (-20.28%)
Hoi Learning ListA list of the Human-Object Interaction Learning studies.
Stars: ✭ 145 (-33.18%)
M PactA one stop shop for all of your activity recognition needs.
Stars: ✭ 85 (-60.83%)