# google-research/frame-interpolation

FILM: Frame Interpolation for Large Motion, In ECCV 2022.

Repository: https://github.com/google-research/frame-interpolation
Canonical: https://ross.abutalabs.com/products/frame-interpolation
Homepage: https://film-net.github.io
Language: Python
License: Apache-2.0
License Family: permissive
Topics: optical-flow, splatting, video, forward-warp, frame-interpolation
Archived: true
Last push: 2024-08-10T01:12:48+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": 1694, "days_push": 754, "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 3150, forks 323 (observed 2026-08-28T04:07:46.120233+00:00)

## What it is
FILM is the official TensorFlow 2 implementation of a state-of-the-art frame interpolation neural network from Google Research, presented at ECCV 2022. It synthesizes smooth slow-motion video from near-duplicate photos or sparse frames, handling large scene motion with a unified single-network approach that requires no pre-trained optical flow or depth models.

## Use cases
- turn near-duplicate photos into slow motion video
- interpolate between two images to generate in-between frames
- smooth out low-framerate video by generating intermediate frames
- high resolution frame interpolation with patch subdivision
- research baseline for large motion frame interpolation

## When to choose
- you need high-quality interpolation across large motion between frames
- you want a TensorFlow-based model with pre-trained checkpoints and a CLI
- you're converting photo sequences into slow-motion footage

## When to avoid
- you need real-time interpolation on CPU-constrained hardware
- you prefer PyTorch tooling
- you need active feature development rather than a maintained research artifact

## Facets
- artifact type: library
- maturity: maintenance
- function: image-processing, video-processing, machine-learning, deep-learning
- domain: computer-vision, machine-learning, media
- platform: python, cross-platform
- tags: frame-interpolation, optical-flow, slow-motion, tensorflow, eccv-2022, video-synthesis, video, gpu

## Member repositories
- google-research/frame-interpolation (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:46.120233+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 2026-08-30T07:25:53.861758+00:00, confidence not recorded.
  - readme: https://github.com/google-research/frame-interpolation (fetched 2026-08-28T04:07:46.120233+00:00, sha 8e3d78f68d95)
  - homepage: https://film-net.github.io (fetched 2026-08-29T09:40:26.653447+00:00, sha 29ae15026fbb)
- Data as of 2026-08-30T08:39:29.467469+00:00.