# Masked Collaborative Contrast for Weakly Supervised Semantic Segmentation

Source: [Masked Collaborative Contrast for Weakly Supervised Semantic Segmentation](<https://www.sota2.com/research/paper/68fa711f1e209131cea4f417>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:58:41.298Z

Authors: Fangwen Wu, Jingxuan He, Yufei Yin, Yanbin Hao, Gang Huang, Lechao Cheng

Published: 2023-05-15T09:46:28.000Z

## Abstract

This study introduces an efficacious approach, Masked Collaborative Contrast (MCC), to highlight semantic regions in weakly supervised semantic segmentation. MCC adroitly draws inspiration from masked image modeling and contrastive learning to devise a novel framework that induces keys to contract toward semantic regions. Unlike prevalent techniques that directly eradicate patch regions in the input image when generating masks, we scrutinize the neighborhood relations of patch tokens by exploring masks considering keys on the affinity matrix. Moreover, we generate positive and negative samples in contrastive learning by utilizing the masked local output and contrasting it with the global output. Elaborate experiments on commonly employed datasets evidences that the proposed MCC mechanism effectively aligns global and local perspectives within the image, attaining impressive performance. The source code is available at \\url{https://github.com/fwu11/MCC}.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Semantic Segmentation on COCO 2014 (val)](<https://www.sota2.com/research/sota/semantic-segmentation-on-coco-2014-val.md>): Semantic segmentation; COCO 2014 (val); mIoU: 42.3.

- [Semantic Segmentation on PASCAL VOC 2012 (test)](<https://www.sota2.com/research/sota/semantic-segmentation-on-pascal-voc-2012-test.md>): Semantic segmentation; PASCAL VOC 2012 (test); mIoU: 71.2.

- [Semantic Segmentation on PASCAL VOC 2012 (val)](<https://www.sota2.com/research/sota/semantic-segmentation-on-pascal-voc-2012-val.md>): Semantic segmentation; PASCAL VOC 2012 (val); Mean IoU: 70.3.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2305.08491>)

[PDF](<https://arxiv.org/pdf/2305.08491.pdf>)