Referring Image Matting

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

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Datasets archive 2025-07-28

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Subtasks archive 2025-07-28

4 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

3 shown of 3 papers with code (3 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Matting Anything
  8 Jun 2023 1 repository listed Syntology ran 2 of 6 samples · 4 unverified
  In this paper, we propose the Matting Anything Model (MAM), an efficient and versatile framework for estimating the alpha matte of any instance in an image with flexible and interactive visual or linguistic user prompt…
• Deep Image Matting: A Comprehensive Survey
  10 Apr 2023 1 repository listed
  Image matting refers to extracting precise alpha matte from natural images, and it plays a critical role in various downstream applications, such as image editing.
• Referring Image Matting
  10 Jun 2022 1 repository listed
  Different from conventional image matting, which either requires user-defined scribbles/trimap to extract a specific foreground object or directly extracts all the foreground objects in the image indiscriminately, we…

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.