piiswrong/deep3d
Automatic 2D-to-3D Video Conversion with CNNs observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3805
- days_rel: n/a
- days_push: 3773
- n_releases_24m: 0
Adoption not part of the score
1299 stars · 254 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Deep3D is a CNN-based research project that automatically converts 2D images and videos into 3D by estimating per-pixel depth maps and generating stereo views. It is implemented as custom MXNet operators with Jupyter Notebook examples.
Use cases
- convert 2d video to 3d automatically
- estimate depth map from a single image
- generate stereo image pairs from 2d photos
- make 3d gifs from regular photos
- research on single-image depth estimation with cnns
When to avoid
- you need a maintained, production-ready 2D-to-3D converter
- you cannot build legacy MXNet with CUDA 7.0 and cuDNN 4
- you want modern deep learning frameworks or pretrained easy-to-use models
Facets
library · maturity abandoned
machine-learning deep-learning image-processing video-processing computer-vision deep-learning computer-vision image-processing python depth-estimation 2d-to-3d mxnet stereo-vision research-code cnn video gpu linux
1 source
- readme: https://github.com/piiswrong/deep3d · fetched 2026-08-28 · 9de97694650a
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| piiswrong/deep3d | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="piiswrong/deep3d")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem