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Cascade Mask R-CNN

23 papers tagged archive 2025-07-28

Introduced by Zhaowei Cai et al. in Cascade R-CNN: Delving into High Quality Object Detection

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

Cascade Mask R-CNN extends Cascade R-CNN to instance segmentation, by adding a mask head to the cascade.

In the Mask R-CNN, the segmentation branch is inserted in parallel to the detection branch. However, the Cascade R-CNN has multiple detection branches. This raises the questions of 1) where to add the segmentation branch and 2) how many segmentation branches to add. The authors consider three strategies for mask prediction in the Cascade R-CNN. The first two strategies address the first question, adding a single mask prediction head at either the first or last stage of the Cascade R-CNN. Since the instances used to train the segmentation branch are the positives of the detection branch, their number varies in these two strategies. Placing the segmentation head later on the cascade leads to more examples. However, because segmentation is a pixel-wise operation, a large number of highly overlapping instances is not necessarily as helpful as for object detection, which is a patch-based operation. The third strategy addresses the second question, adding a segmentation branch to each cascade stage. This maximizes the diversity of samples used to learn the mask prediction task.

At inference time, all three strategies predict the segmentation masks on the patches produced by the final object detection stage, irrespective of the cascade stage on which the segmentation mask is implemented and how many segmentation branches there are.

PaperSource

Papers archive 2025-07-28

23 shown of 23, 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

20 shown of 28 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 Segmentation14
Object Detection14
Semantic Segmentation12
object-detection10
Segmentation8
Object3
Binarization2
Data Augmentation2
Image Augmentation2
Image Classification2
Table Detection2
Transfer Learning2
Video Instance Segmentation2
2D Object Detection1
Classification1
Deep Learning1
Diversity1
Document Layout Analysis1
Image Segmentation1
Knowledge Distillation1

Usage over time archive 2025-07-28

Papers per year tagged with Cascade Mask R-CNN: 2017 to 2025, peak 8 8 0 2017: 1 paper 2017 2018: 0 papers 2018 2019: 3 papers 2019 2020: 3 papers 2020 2021: 8 papers 2021 2022: 2 papers 2022 2023: 4 papers 2023 2024: 0 papers 2024 2025: 2 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (23 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 Models

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