Methods › Computer Vision › Instance Segmentation Modules › Implicit PointRend

Implicit PointRend

1 paper tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Implicit PointRend is a modification to the PointRend module for instance segmentation. Instead of a coarse mask prediction used in PointRend to provide region-level context to distinguish objects, for each object Implicit PointRend generates different parameters for a function that makes the final pointwise mask prediction. The new model is more straightforward than PointRend: (1) it does not require an importance point sampling during training and (2) it uses a single point-level mask loss instead of two mask losses. Implicit PointRend can be trained directly with point supervision without any intermediate prediction interpolation steps.

Source: Pointly-Supervised Instance Segmentation

Papers archive 2025-07-28

1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Instance Segmentation1
Object1
Segmentation1
Semantic Segmentation1
Weakly-supervised instance segmentation1

Usage over time archive 2025-07-28

Papers per year tagged with Implicit PointRend: 2021 to 2021, peak 1 1 0 2021: 1 paper 2021
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Instance Segmentation Modules

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