# avinashpaliwal/Super-SloMo

PyTorch implementation of Super SloMo by Jiang et al.

Repository: https://github.com/avinashpaliwal/Super-SloMo
Canonical: https://ross.abutalabs.com/products/super-slomo
Language: Python
License: MIT
License Family: permissive
Topics: video-frame-interpolation, super-slomo, pytorch-implmention, pytorch, slow-motion, deep-learning, deep-neural-networks, convolutional-neural-networks, frame-interpolation, slomo
Archived: true
Last push: 2023-03-09T18:39:45+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2808, "days_push": 1273, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3025, forks 481 (observed 2026-08-28T04:07:38.689416+00:00)

## What it is
A PyTorch implementation of the Super SloMo paper for high-quality video frame interpolation, generating multiple intermediate frames to convert videos into slow motion. It includes training scripts, pretrained models, and an evaluation pipeline.

## Use cases
- convert a normal video to slow motion
- interpolate intermediate frames between existing video frames
- increase video frame rate with a neural network
- train a video frame interpolation model on a custom dataset
- evaluate frame interpolation models on UCF101
- reproduce Super SloMo research results

## When to choose
- you need deep-learning-based video frame interpolation in PyTorch
- you want to reproduce or build on the Super SloMo paper
- you have a GPU and want high-quality slow-motion conversion

## When to avoid
- you need a maintained production tool with modern PyTorch support
- you want real-time interpolation on CPU
- you need a simple CLI without deep learning dependencies

## Facets
- artifact type: library
- maturity: maintenance
- function: video-processing, machine-learning, deep-learning, image-processing
- domain: computer-vision, deep-learning, machine-learning
- platform: python, cross-platform
- tags: video-frame-interpolation, slow-motion, pytorch, neural-networks, research-code, frame-interpolation, video, gpu, linux

## Member repositories
- avinashpaliwal/Super-SloMo (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:38.689416+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:29:53.891162+00:00, confidence not recorded.
  - readme: https://github.com/avinashpaliwal/Super-SloMo (fetched 2026-08-28T04:07:38.689416+00:00, sha 86a4a1eb81e7)
- Data as of 2026-08-30T08:39:29.467469+00:00.