Vidvrd HelperTo keep updates with VRU Grand Challenge, please use https://github.com/NExTplusplus/VidVRD-helper
Stars: ✭ 81 (-96.59%)
torch-lrcnAn implementation of the LRCN in Torch
Stars: ✭ 85 (-96.43%)
Hake ActionAs a part of the HAKE project, includes the reproduced SOTA models and the corresponding HAKE-enhanced versions (CVPR2020).
Stars: ✭ 72 (-96.97%)
TadTREnd-to-end Temporal Action Detection with Transformer. [Under review for a journal publication]
Stars: ✭ 55 (-97.69%)
Fight detectionReal time Fight Detection Based on 2D Pose Estimation and RNN Action Recognition
Stars: ✭ 65 (-97.27%)
video repres mascode for CVPR-2019 paper: Self-supervised Spatio-temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics
Stars: ✭ 63 (-97.35%)
I3d finetuneTensorFlow code for finetuning I3D model on UCF101.
Stars: ✭ 128 (-94.62%)
Resgcnv1ResGCN: an efficient baseline for skeleton-based human action recognition.
Stars: ✭ 50 (-97.9%)
VipVideo Platform for Action Recognition and Object Detection in Pytorch
Stars: ✭ 175 (-92.64%)
Okutama ActionOkutama-Action: An Aerial View Video Dataset for Concurrent Human Action Detection
Stars: ✭ 36 (-98.49%)
Pose2vecA Repository for maintaining various human skeleton preprocessing steps in numpy and tensorflow along with tensorflow model to learn pose embeddings.
Stars: ✭ 25 (-98.95%)
pose2actionexperiments on classifying actions using poses
Stars: ✭ 24 (-98.99%)
gzsl-odOut-of-Distribution Detection for Generalized Zero-Shot Action Recognition
Stars: ✭ 47 (-98.02%)
TimeceptionTimeception for Complex Action Recognition, CVPR 2019 (Oral Presentation)
Stars: ✭ 153 (-93.57%)
tfvaegan[ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL
Stars: ✭ 107 (-95.5%)
Hcn Prototypeloss PytorchHierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)
Stars: ✭ 17 (-99.29%)
dynamic-images-for-action-recognitionA public Python implementation for generating Dynamic Images introduced in 'Dynamic Image Networks for Action Recognition' by Bilen et al.
Stars: ✭ 27 (-98.86%)
ModelfeastPytorch model zoo for human, include all kinds of 2D CNN, 3D CNN, and CRNN
Stars: ✭ 116 (-95.12%)
MTL-AQAWhat and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment [CVPR 2019]
Stars: ✭ 38 (-98.4%)
Two Stream Action RecognitionUsing two stream architecture to implement a classic action recognition method on UCF101 dataset
Stars: ✭ 705 (-70.35%)
Openpose-based-GUI-for-Realtime-Pose-Estimate-and-Action-RecognitionGUI based on the python api of openpose in windows using cuda10 and cudnn7. Support body , hand, face keypoints estimation and data saving. Realtime gesture recognition is realized through two-layer neural network based on the skeleton collected from the gui.
Stars: ✭ 69 (-97.1%)
AmassData preparation and loader for AMASS
Stars: ✭ 180 (-92.43%)
ViCC[WACV'22] Code repository for the paper "Self-supervised Video Representation Learning with Cross-Stream Prototypical Contrasting", https://arxiv.org/abs/2106.10137.
Stars: ✭ 33 (-98.61%)
MSAFOffical implementation of paper "MSAF: Multimodal Split Attention Fusion"
Stars: ✭ 47 (-98.02%)
TddTrajectory-pooled Deep-Convolutional Descriptors
Stars: ✭ 99 (-95.84%)
VideoTransformer-pytorchPyTorch implementation of a collections of scalable Video Transformer Benchmarks.
Stars: ✭ 159 (-93.31%)
Gluon CvGluon CV Toolkit
Stars: ✭ 5,001 (+110.3%)
C3D-tensorflowAction recognition with C3D network implemented in tensorflow
Stars: ✭ 34 (-98.57%)
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 (-82.46%)
auditory-slow-fastImplementation of "Slow-Fast Auditory Streams for Audio Recognition, ICASSP, 2021" in PyTorch
Stars: ✭ 46 (-98.07%)
Video Dataset Loading PytorchGeneric PyTorch Dataset Implementation for Loading, Preprocessing and Augmenting Video Datasets
Stars: ✭ 92 (-96.13%)
temporal-sslVideo Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.
Stars: ✭ 46 (-98.07%)
TA3N[ICCV 2019 Oral] TA3N: https://github.com/cmhungsteve/TA3N (Most updated repo)
Stars: ✭ 45 (-98.11%)
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 (-92.77%)
LintelA Python module to decode video frames directly, using the FFmpeg C API.
Stars: ✭ 240 (-89.91%)
Ms G3d[CVPR 2020 Oral] PyTorch implementation of "Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition"
Stars: ✭ 225 (-90.54%)
Ican[BMVC 2018] iCAN: Instance-Centric Attention Network for Human-Object Interaction Detection
Stars: ✭ 225 (-90.54%)
Ta3n[ICCV 2019 (Oral)] Temporal Attentive Alignment for Large-Scale Video Domain Adaptation (PyTorch)
Stars: ✭ 217 (-90.87%)
DIN-Group-Activity-Recognition-BenchmarkA new codebase for Group Activity Recognition. It contains codes for ICCV 2021 paper: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition and some other methods.
Stars: ✭ 26 (-98.91%)
Hidden Two StreamCaffe implementation for "Hidden Two-Stream Convolutional Networks for Action Recognition"
Stars: ✭ 179 (-92.47%)
C3d KerasC3D for Keras + TensorFlow
Stars: ✭ 171 (-92.81%)
HakeHAKE: Human Activity Knowledge Engine (CVPR'18/19/20, NeurIPS'20)
Stars: ✭ 132 (-94.45%)