baowenbo/DAIN

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

8316 stars · 834 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

DAIN is a PyTorch-based deep learning model for depth-aware video frame interpolation, synthesizing intermediate frames between existing ones while handling occlusion via depth cues. It is the official research code from a CVPR 2019 paper, including pre-trained models and training scripts.

Use cases

• interpolate missing frames in a video
• convert video to slow motion
• increase video frame rate with AI
• smooth choppy low-fps footage
• research video frame interpolation models
• generate in-between frames handling occlusion

When to choose

• you need high-quality frame interpolation that handles occlusion and large motion
• you want a research-grade model with pre-trained weights and training code
• you have a GPU and want to generate slow-motion or fps-boosted videos

When to avoid

• you need a fast, actively maintained tool with modern GPU support
• you want real-time interpolation or a simple GUI application
• your project requires recent deep learning framework versions out of the box

Facets

library · maturity maintenance

video-processing machine-learning image-processing computer-vision deep-learning media python video-frame-interpolation optical-flow depth-estimation slow-motion cvpr-2019 research-code video linux gpu

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markdown · JSON · MCP: product_card(name="baowenbo/DAIN")