3D-ResNets-PyTorch and 3D-ResNets

These two tools are ecosystem siblings, where the PyTorch implementation (A) is the actively developed and more popular version of the original 3D ResNets project (B) by the same author, likely reflecting a migration or specific framework focus.

3D-ResNets-PyTorch
51
Established
3D-ResNets
44
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 18/25
Stars: 4,043
Forks: 935
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 122
Forks: 21
Downloads: —
Commits (30d): 0
Language: Lua
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About 3D-ResNets-PyTorch

kenshohara/3D-ResNets-PyTorch

3D ResNets for Action Recognition (CVPR 2018)

This project helps researchers and engineers analyze video content by automatically recognizing actions performed in video clips. It takes raw video files or image sequences as input and outputs a classification of the actions detected. The primary users are professionals working with large video datasets, such as those in computer vision research, surveillance, or content moderation.

video-analytics action-recognition computer-vision video-content-analysis behavioral-analysis

About 3D-ResNets

kenshohara/3D-ResNets

3D ResNets for Action Recognition

This project helps researchers and developers working with video data to train and test advanced AI models that can automatically identify actions happening within video clips. It takes video files, converts them into image sequences, and then processes these sequences to recognize specific human activities or events. This is primarily for computer vision researchers and AI model trainers focused on video analysis.

video-analysis action-recognition computer-vision machine-learning-research deep-learning-training

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