# Weakly Supervised Semantic Segmentation using Web-Crawled Videos

Source: [Weakly Supervised Semantic Segmentation using Web-Crawled Videos](<https://www.sota2.com/research/paper/68fa63eb1e209131cea01751>)

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

Data updated: 2025-10-25T20:52:10.607Z

Authors: Seunghoon Hong, Donghun Yeo, Suha Kwak, Honglak Lee, Bohyung Han

Published: 2017-01-02T10:12:03.000Z

## Abstract

We propose a novel algorithm for weakly supervised semantic segmentation based on image-level class labels only. In weakly supervised setting, it is commonly observed that trained model overly focuses on discriminative parts rather than the entire object area. Our goal is to overcome this limitation with no additional human intervention by retrieving videos relevant to target class labels from web repository, and generating segmentation labels from the retrieved videos to simulate strong supervision for semantic segmentation. During this process, we take advantage of image classification with discriminative localization technique to reject false alarms in retrieved videos and identify relevant spatio-temporal volumes within retrieved videos. Although the entire procedure does not require any additional supervision, the segmentation annotations obtained from videos are sufficiently strong to learn a model for semantic segmentation. The proposed algorithm substantially outperforms existing methods based on the same level of supervision and is even as competitive as the approaches relying on extra annotations.

## 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: 58.7.

- [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: 58.1.

- [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: 58.7.

- [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: 58.1.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1701.00352>)

[PDF](<https://arxiv.org/pdf/1701.00352.pdf>)