Papers › Mining Latent Classes for Few-shot Segmentation

Mining Latent Classes for Few-shot Segmentation

29 Mar 2021ICCV 2021 10arXiv:2103.15402archive 2025-07-28

Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao

Few-shot segmentation (FSS) aims to segment unseen classes given only a few annotated samples. Existing methods suffer the problem of feature undermining, i.e. potential novel classes are treated as background during training phase. Our method aims to alleviate this problem and enhance the feature embedding on latent novel classes. In our work, we propose a novel joint-training framework. Based on conventional episodic training on support-query pairs, we add an additional mining branch that exploits latent novel classes via transferable sub-clusters, and a new rectification technique on both background and foreground categories to enforce more stable prototypes. Over and above that, our transferable sub-cluster has the ability to leverage extra unlabeled data for further feature enhancement. Extensive experiments on two FSS benchmarks demonstrate that our method outperforms previous state-of-the-art by a large margin of 3.7% mIOU on PASCAL-5i and 7.0% mIOU on COCO-20i at the cost of 74% fewer parameters and 2.5x faster inference speed. The source code is available at https://github.com/LiheYoung/MiningFSS.

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Tasks

Few-Shot Semantic Segmentation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Few-Shot Semantic Segmentation COCO-20i (1-shot) MLC (ResNet-101) Mean IoU 37.5 #68 of 85 Archive leaderboard report
Few-Shot Semantic Segmentation COCO-20i (1-shot) MLC (ResNet-50) Mean IoU 35.1 #73 of 85 Archive leaderboard report
Few-Shot Semantic Segmentation COCO-20i (5-shot) MLC (ResNet-101) Mean IoU 45.1 #62 of 81 Archive leaderboard report
Few-Shot Semantic Segmentation COCO-20i (5-shot) MLC (ResNet-50) Mean IoU 41.4 #71 of 81 Archive leaderboard report
Few-Shot Semantic Segmentation PASCAL-5i (1-Shot) MLC (ResNet-101) Mean IoU 63.8 #65 of 105 Archive leaderboard report
Few-Shot Semantic Segmentation PASCAL-5i (1-Shot) MLC (ResNet-50) Mean IoU 63.6 #66 of 105 Archive leaderboard report
Few-Shot Semantic Segmentation PASCAL-5i (5-Shot) MLC (ResNet-101) Mean IoU 69.3 #49 of 96 Archive leaderboard report
Few-Shot Semantic Segmentation PASCAL-5i (5-Shot) MLC (ResNet-50) Mean IoU 66.8 #65 of 96 Archive leaderboard report

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