No. 15 of 28 ·AI Video Background Removers

MatAnyone

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Freedom report

One barScore 5.3

Free tierNo free tier on record
Open codeNo open-source code on record
Runs widely1 of 6 device platforms
DocumentedPlans, terms and facts published

MatAnyone is ranked #15 of 28 in AI video background removers on Freedom251. It runs on Self-hosted, Web.

Compared on AI video background removers

Foreground isolation: Yes
Max export resolution: 1080p
Video input formats: .mp4, .mov, .avi

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The record

Product: MatAnyone is a practical human video matting framework that supports assigning a target and produces stable core regions and fine-grained boundary details.
Inputs and outputs: Inference takes a video and its first-frame segmentation mask and outputs foreground and alpha videos.
Multiple targets: The inference scripts support processing multiple targets by using separate masks.
Interactive demo: The Gradio demo lets users upload a video or image and assign target masks with a few clicks; it can run on Hugging Face or locally.
Integrations: The project provides Hugging Face model loading and a Hugging Face demo, and references SAM2 as an example source of segmentation masks.
Local setup: The repository documents installation with Conda and Python 3.8, plus an optional dependency set for the Gradio demo.
Video formats: The example inputs include MP4, MOV, and AVI video files.
Resolution handling: Input resolution has no maximum by default, but users can set a maximum size that downsamples larger videos.
License: The project uses the S-Lab License 1.0, which permits non-commercial use; commercial use requires contacting the contributors.
Security and trust: The project pages opened for this research do not state security certifications or compliance claims.
Support: The repository invites questions by email at [email protected].
Research context: The project page identifies MatAnyone as a CVPR 2025 paper and lists the authors’ affiliations as S-Lab at Nanyang Technological University and SenseTime Research.
Research use: The repository provides training instructions, evaluation scripts, benchmark data, and asks users to cite the CVPR paper when using the repository for research.

Where it ranks on Freedom251

Best AI Video Background Removers in 2026#15 of 28

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Sources

github.com/pq-yang/MatAnyone· checked 4 Oct 2026
github.com/pq-yang/MatAnyone/blob/main/LICENSE· checked 4 Oct 2026
pq-yang.github.io/projects/MatAnyone/· checked 4 Oct 2026