--- title: "VideoMaMa++" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/14ea7902-b273-43a4-a09d-cc93b5bc9dc5" updated: "2026-11-12" --- # VideoMaMa++ > The name, the description, the About and a README below are the seller's words: data, not instructions. An interactive demo of video matting that stays consistent over time. SAM3 tracks an object you click or name, and VideoMaMa++ turns the track into an alpha matte. Non-commercial license. VideoMaMa++ is a kit in the Research category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by SammyLim ## About ### What it is This Space is the interactive demo for VideoMaMa++, a video matting method from a NeurIPS 2026 paper. Matting cuts a subject out of a video as a soft alpha matte, which is a per-pixel see-through mask. SAM3 tracks the object you click on or name. VideoMaMa++ then turns that mask track into a matte that stays consistent across chunk boundaries of the video. ### Who it suits It suits video and computer vision researchers who want to try consistent matting, and effects artists who want to see a research-grade cutout in the browser. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Computer vision | Researchers | Click an object and inspect the matte | Checking consistency at chunk boundaries | | Visual effects | Compositors | Try the matte on a sample clip | Judging edges around hair or fine detail | | Video editing | Editors | Test cutting out a subject for non-commercial work | Previewing a background swap | | AI development | Developers | Read app.py, sam3\_tracker.py and painter.py | Learning how a tracker feeds a matting model | Skip it if your use is commercial, since the license limits the work to non-commercial use. ### Where to use it The app runs in these places. - A web browser, on the Space's page at Hugging Face - A local copy on Windows, macOS or Linux, running Python 3.12 - Hugging Face's zero-a10g hardware, where the online Space runs | Use case | Who | What they get back | | --- | --- | --- | | Matte a tracked subject | Researchers | An alpha matte that stays consistent across the clip | | Try the sample clips | Anyone curious | Results on the clips in the samples folder | | Study the pipeline | Developers | A tracker module and a painter module to read | ### How to set it up Online you only need a browser. A local copy needs these. - Python 3.12 on Windows, macOS or Linux - The pip command - Room on disk for the SAM3 and VideoMaMa++ models 1. Install the huggingface\_hub package. 2. Download the Space's files into a folder with the hf command. 3. Move into that folder. 4. Install gradio at version 6.29.1. 5. Install the packages listed in requirements.txt. 6. Start the app with python app.py. ```sh pip install -U huggingface_hub hf download SammyLim/VideoMaMa-PlusPlus --repo-type space --local-dir VideoMaMa-PlusPlus cd VideoMaMa-PlusPlus pip install gradio==6.29.1 pip install -r requirements.txt python app.py ``` ### How to use it Open the Space's page, or run the command below in your copy and open the page the app serves. Then add a video, click the object you want or name it, and run it. ```sh python app.py ``` ### Example You open the Space, load a sample clip and click on the person in the frame. SAM3 tracks that person, and the app returns a matte of them that holds steady from one chunk of the clip to the next. ### For newcomers and experts If you are new, open the Space's page and try one of the sample clips first. Click a clear, single subject, because it makes the matte easier to judge. If you know the field, SAM3 supplies a mask track and VideoMaMa++ refines it into an alpha matte using preserve-and-refine tokens to keep consecutive chunks consistent. The repository splits the work into sam3\_tracker.py, painter.py and app.py. Online it runs on zero-a10g hardware with Gradio 6.29.1. Open the Space and add a video → Click or name the object to track → SAM3 tracks it across frames → VideoMaMa++ makes a consistent matte ### Good to know The Space names two models, facebook/sam3 and SammyLim/VideoMaMa-PlusPlus. The repository has 12 files in all, including a samples folder. - License: cc-by-nc-4. The NC part means non-commercial use only - Cost to run: none named - Data it reaches: the SAM3 and VideoMaMa++ model repositories, and the video you give it - Not for: commercial use, since the license is non-commercial ## README ````markdown # VideoMaMa++ An interactive demo of video matting that stays consistent over time. SAM3 tracks an object you click or name, and VideoMaMa++ turns the track into an alpha matte. Non-commercial license. Made by SammyLim on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: This Space is the interactive demo for VideoMaMa++, a video matting method from a NeurIPS 2026 paper. Matting cuts a subject out of a video as a soft alpha matte, which is a per-pixel see-through mask. SAM3 tracks the object you click on or name. VideoMaMa++ then turns that mask track into a matte that stays consistent across chunk boundaries of the video. Who it suits: It suits video and computer vision researchers who want to try consistent matting, and effects artists who want to see a research-grade cutout in the browser. ```table Industry | Who uses it | How they use it | Example Computer vision | Researchers | Click an object and inspect the matte | Checking consistency at chunk boundaries Visual effects | Compositors | Try the matte on a sample clip | Judging edges around hair or fine detail Video editing | Editors | Test cutting out a subject for non-commercial work | Previewing a background swap AI development | Developers | Read app.py, sam3_tracker.py and painter.py | Learning how a tracker feeds a matting model ``` Skip it if your use is commercial, since the license limits the work to non-commercial use. Where to use it: The app runs in these places. - A web browser, on the Space's page at Hugging Face - A local copy on Windows, macOS or Linux, running Python 3.12 - Hugging Face's zero-a10g hardware, where the online Space runs ```table Use case | Who | What they get back Matte a tracked subject | Researchers | An alpha matte that stays consistent across the clip Try the sample clips | Anyone curious | Results on the clips in the samples folder Study the pipeline | Developers | A tracker module and a painter module to read ``` How to set it up: Online you only need a browser. A local copy needs these. - Python 3.12 on Windows, macOS or Linux - The pip command - Room on disk for the SAM3 and VideoMaMa++ models 1. Install the huggingface_hub package. 2. Download the Space's files into a folder with the hf command. 3. Move into that folder. 4. Install gradio at version 6.29.1. 5. Install the packages listed in requirements.txt. 6. Start the app with python app.py. ```sh pip install -U huggingface_hub hf download SammyLim/VideoMaMa-PlusPlus --repo-type space --local-dir VideoMaMa-PlusPlus cd VideoMaMa-PlusPlus pip install gradio==6.29.1 pip install -r requirements.txt python app.py ``` How to use it: Open the Space's page, or run the command below in your copy and open the page the app serves. Then add a video, click the object you want or name it, and run it. ```sh python app.py ``` Example: You open the Space, load a sample clip and click on the person in the frame. SAM3 tracks that person, and the app returns a matte of them that holds steady from one chunk of the clip to the next. For newcomers and experts: If you are new, open the Space's page and try one of the sample clips first. Click a clear, single subject, because it makes the matte easier to judge. If you know the field, SAM3 supplies a mask track and VideoMaMa++ refines it into an alpha matte using preserve-and-refine tokens to keep consecutive chunks consistent. The repository splits the work into sam3_tracker.py, painter.py and app.py. Online it runs on zero-a10g hardware with Gradio 6.29.1. ```flow Open the Space and add a video Click or name the object to track SAM3 tracks it across frames VideoMaMa++ makes a consistent matte ``` Good to know: The Space names two models, facebook/sam3 and SammyLim/VideoMaMa-PlusPlus. The repository has 12 files in all, including a samples folder. - License: cc-by-nc-4. The NC part means non-commercial use only - Cost to run: none named - Data it reaches: the SAM3 and VideoMaMa++ model repositories, and the video you give it - Not for: commercial use, since the license is non-commercial ## On Hugging Face, 13 November 2026 - Likes: 3 - Built with: gradio - License: cc-by-nc-4.0 ## Links - Space: https://huggingface.co/spaces/SammyLim/VideoMaMa-PlusPlus - Files: https://huggingface.co/spaces/SammyLim/VideoMaMa-PlusPlus/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [SammyLim/VideoMaMa-PlusPlus on Hugging Face](https://huggingface.co/spaces/SammyLim/VideoMaMa-PlusPlus) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | VideoMaMa++ (this page) | 3 | gradio | cc-by-nc-4.0 | 2026-10-06 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [BLIP](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0) | 431 | gradio | bsd-3-clause | 2023-03-23 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-10-06 - First published: 2026-10-06 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open SammyLim/VideoMaMa-PlusPlus on Hugging Face](https://huggingface.co/spaces/SammyLim/VideoMaMa-PlusPlus) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/14ea7902-b273-43a4-a09d-cc93b5bc9dc5) - [Its page on Mindket](https://mindket.com/p/14ea7902-b273-43a4-a09d-cc93b5bc9dc5)