# Discovering Class-Specific Pixels for Weakly-Supervised Semantic Segmentation

Source: [Discovering Class-Specific Pixels for Weakly-Supervised Semantic Segmentation](<https://www.sota2.com/research/paper/68fa64c01e209131cea064bb>)

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

Data updated: 2025-10-25T21:10:58.701Z

Authors: Arslan Chaudhry, Puneet K. Dokania, Philip H.S. Torr

Published: 2017-07-18T19:03:22.000Z

## Abstract

We propose an approach to discover class-specific pixels for the weakly-supervised semantic segmentation task. We show that properly combining saliency and attention maps allows us to obtain reliable cues capable of significantly boosting the performance. First, we propose a simple yet powerful hierarchical approach to discover the class-agnostic salient regions, obtained using a salient object detector, which otherwise would be ignored. Second, we use fully convolutional attention maps to reliably localize the class-specific regions in a given image. We combine these two cues to discover class-specific pixels which are then used as an approximate ground truth for training a CNN. While solving the weakly supervised semantic segmentation task, we ensure that the image-level classification task is also solved in order to enforce the CNN to assign at least one pixel to each object present in the image. Experimentally, on the PASCAL VOC12 val and test sets, we obtain the mIoU of 60.8% and 61.9%, achieving the performance gains of 5.1% and 5.2% compared to the published state-of-the-art results. The code is made publicly available.

## 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.

- [Weakly Supervised Semantic Segmentation on PASCAL VOC 2012 (test)](<https://www.sota2.com/research/sota/weakly-supervised-semantic-segmentation-on-pascal-voc-2012-test.md>): Weakly supervised semantic segmentation; PASCAL VOC 2012 (test); mIoU: 61.9.

- [Weakly Supervised Semantic Segmentation on PASCAL VOC 2012 (val)](<https://www.sota2.com/research/sota/weakly-supervised-semantic-segmentation-on-pascal-voc-2012-val.md>): Weakly supervised semantic segmentation; PASCAL VOC 2012 (val); mIoU: 60.8.

- [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: 61.9.

- [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: 60.8.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1707.05821>)

[PDF](<https://arxiv.org/pdf/1707.05821.pdf>)