Royalvice/DocDiff

ACM Multimedia 2023: DocDiff: Document Enhancement via Residual Diffusion Models. Also contains 1597 red seals in Chinese scenes, along with their corresponding binary masks.

343 32 +0/wk

GitHub

dataset deblurring deep-learning diffusion-models document-binarization documentation-tool image-to-image image-translation img2img low-level-vision math-ocr ocr

Trend 0

Star & Fork Trend (18 data points)

Stars

Forks

Multi-Source Signals

GitHub

stars 343

forks 32

Growth Velocity

Royalvice/DocDiff has +0 stars this period . Velocity data will be available after more historical data is collected.

Deep analysis is being generated for this repository.

Signal-backed technical analysis will be available soon.

Metric	DocDiff	PortaSpeech	Build-a-Large-Language-Model-from-Scratch	RL-Theory-book
Stars	343	342	345	345
Forks	32	38	84	21
Weekly Growth	+0	+0	+0	+1
Language	Python	Python	Python	TeX
Sources	1	1	1	1
License	MIT	MIT	N/A	N/A

Capability Radar vs PortaSpeech

DocDiff

PortaSpeech

Maintenance Activity 0

Last code push 595 days ago.

Community Engagement 47

Fork-to-star ratio: 9.3%. Lower fork ratio may indicate passive usage.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 95

Licensed under MIT. Permissive — safe for commercial use.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.