# Daisy-Zhang/Awesome-Deepfakes-Detection

A list of tools, papers and code related to Deepfake Detection.

Repository: https://github.com/Daisy-Zhang/Awesome-Deepfakes-Detection
Canonical: https://ross.abutalabs.com/products/awesome-deepfakes-detection
License: MIT
License Family: permissive
Topics: awesome, deepfakes, deepfake-detection, dataset, paperlist, tools, code, paper-with-code, image, video
Last push: 2025-09-02T01:56:45+00:00

## Health v2 (maintenance only)
Score: 50/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 39, release rhythm 35, longevity 100
- inputs: {"age_days": 1890, "days_push": 366, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1817, forks 165 (observed 2026-08-28T04:05:40.608630+00:00)

## What it is
A curated awesome-list of datasets, tools, papers, and code for deepfake detection research. It organizes resources by method categories such as frequency-based, spatiotemporal, robustness, and interpretability.

## Use cases
- find datasets for training deepfake detection models
- survey recent papers on face forgery detection
- locate code implementations of deepfake detectors
- compare deepfake detection benchmarks like Celeb-DF and FaceForensics
- research robustness of deepfake detectors to real-world scenarios
- find tools for detecting manipulated face images and videos

## When to choose
- starting research on deepfake detection and needing a literature map
- looking for benchmark datasets for face forgery forensics
- tracking recent conference papers on media manipulation detection

## When to avoid
- you need a ready-to-run detection model rather than a resource list
- you want deepfake generation resources (see Awesome Deepfakes instead)
- you need production-grade media forensics tooling

## Facets
- artifact type: learning-resource
- maturity: active
- function: computer-vision, image-processing, video-processing, machine-learning, deep-learning
- domain: artificial-intelligence, computer-vision, deep-learning, security, awesome-lists
- platform: cross-platform
- tags: awesome-list, deepfakes, deepfake-detection, paper-list, datasets, media-forensics, face-forgery

## Member repositories
- Daisy-Zhang/Awesome-Deepfakes-Detection (main) score 50

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:40.608630+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 2026-08-30T03:20:10.349636+00:00, confidence not recorded.
  - readme: https://github.com/Daisy-Zhang/Awesome-Deepfakes-Detection (fetched 2026-08-28T04:05:40.608630+00:00, sha 2343c1784658)
- Data as of 2026-08-30T08:39:29.467469+00:00.