# Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning Source: [Weakly-Supervised Semantic Segmentation by Iterative Affinity Learning]() Collection index: [llms.txt]() Data updated: 2025-10-25T22:06:19.934Z Authors: Xiang Wang, Sifei Liu, Huimin Ma, Ming-Hsuan Yang Published: 2020-02-19T10:32:03.000Z ## Abstract Weakly-supervised semantic segmentation is a challenging task as no pixel-wise label information is provided for training. Recent methods have exploited classification networks to localize objects by selecting regions with strong response. While such response map provides sparse information, however, there exist strong pairwise relations between pixels in natural images, which can be utilized to propagate the sparse map to a much denser one. In this paper, we propose an iterative algorithm to learn such pairwise relations, which consists of two branches, a unary segmentation network which learns the label probabilities for each pixel, and a pairwise affinity network which learns affinity matrix and refines the probability map generated from the unary network. The refined results by the pairwise network are then used as supervision to train the unary network, and the procedures are conducted iteratively to obtain better segmentation progressively. To learn reliable pixel affinity without accurate annotation, we also propose to mine confident regions. We show that iteratively training this framework is equivalent to optimizing an energy function with convergence to a local minimum. Experimental results on the PASCAL VOC 2012 and COCO datasets demonstrate that the proposed algorithm performs favorably against the state-of-the-art methods. ## 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)](): Weakly supervised semantic segmentation; PASCAL VOC 2012 (test); mIoU: 65.4. - [Weakly Supervised Semantic Segmentation on PASCAL VOC 2012 (val)](): Weakly supervised semantic segmentation; PASCAL VOC 2012 (val); mIoU: 64.3. - [Semantic Segmentation on COCO (val)](): Semantic segmentation; COCO (val); mIoU: 27.7. - [Semantic Segmentation on COCO 2014 (val)](): Semantic segmentation; COCO 2014 (val); mIoU: 27.7. - [Semantic Segmentation on PASCAL VOC 2012 (test)](): Semantic segmentation; PASCAL VOC 2012 (test); mIoU: 65.4. - [Semantic Segmentation on PASCAL VOC 2012 (val)](): Semantic segmentation; PASCAL VOC 2012 (val); Mean IoU: 64.3. ## Original sources and implementation [Original paper]() [PDF]()