OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
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Updated
May 16, 2024 - Python
OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
Inflated i3d network with inception backbone, weights transfered from tensorflow
Extract video features from raw videos using multiple GPUs. We support RAFT flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, ResNet features.
Source code for "Bi-modal Transformer for Dense Video Captioning" (BMVC 2020)
Transforms for video datasets in pytorch
TensorFlow code for finetuning I3D model on UCF101.
Pytorch model zoo for human, include all kinds of 2D CNN, 3D CNN, and CRNN
Video Platform for Action Recognition and Object Detection in Pytorch
Sign Language Recognition for Deaf People
I3D and 3D-ResNets in PyTorch
A one stop shop for all of your activity recognition needs.
Rewriting the I3D blender addon from scratch and adding long-sought community features
PyTorch implementation of Multi-modal Dense Video Captioning (CVPR 2020 Workshops)
Video Classification based on PyTorch
I3D implemetation in Keras + video preprocessing + visualization of results
Tool used for extracting the binary .i3d.shapes files used by the GIANTS engine
Multiple driving action prediction model using Faster-RCNN and object-centric network.
[CVPR2020] Clean-Label Backdoor Attacks on Video Recognition Models
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