3D ResNets for Action Recognition
3D ResNets for Action Recognition (CVPR 2018) observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3275
- days_rel: n/a
- days_push: 2051
- n_releases_24m: 0
Adoption not part of the score
4038 stars · 926 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
A PyTorch implementation of 3D ResNet and R(2+1)D models for video action recognition, accompanying CVPR 2018 and related papers. It includes training, fine-tuning, and evaluation scripts plus pretrained models on Kinetics-700, Moments in Time, and STAIR-Actions.
Use cases
- classify human actions in videos
- fine-tune a 3D CNN on my own video dataset
- get pretrained Kinetics video models
- train 3D ResNets on UCF-101 or HMDB-51
- extract spatiotemporal features from video clips
- reproduce CVPR 2018 action recognition results
When to choose
- you need proven 3D CNN baselines for video action recognition
- you want pretrained Kinetics/Moments in Time models in PyTorch
- you are doing research on spatiotemporal video models
When to avoid
- you need real-time or production video inference with minimal setup
- you want actively maintained code with recent PyTorch support
- you need lightweight 2D image classification instead of video
Facets
library · maturity maintenance
deep-learning computer-vision video-processing machine-learning computer-vision deep-learning machine-learning python pytorch action-recognition 3d-cnn resnet video-classification pretrained-models kinetics video linux gpu
1 source
- readme: https://github.com/kenshohara/3D-ResNets-PyTorch · fetched 2026-08-28 · d9ea4c43a4e1
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| kenshohara/3D-ResNets-PyTorch | main | 23 |
| kenshohara/video-classification-3d-cnn-pytorch | plugin | 32 |
For agents
markdown · JSON · MCP: product_card(name="kenshohara/3D-ResNets-PyTorch")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem