Methods › Computer Vision › One-Stage Object Detection Models › RetinaMask

RetinaMask

1 paper tagged archive 2025-07-28

Introduced by Cheng-Yang Fu et al. in RetinaMask: Learning to predict masks improves state-of-the-art single-shot detection for free

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

RetinaMask is a one-stage object detection method that improves upon RetinaNet by adding the task of instance mask prediction during training, as well as an adaptive loss that improves robustness to parameter choice during training, and including more difficult examples in training.

PaperSourceSee Code · chengyangfu/retinamask

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

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

TaskPapers
Object Detection1

Usage over time archive 2025-07-28

Papers per year tagged with RetinaMask: 2019 to 2019, peak 1 1 0 2019: 1 paper 2019
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

One-Stage Object Detection ModelsObject Detection Models

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections