Papers › Weakly Supervised Instance Segmentation by Deep Community Learning

Weakly Supervised Instance Segmentation by Deep Community Learning

30 Jan 2020arXiv:2001.11207archive 2025-07-28

Jaedong Hwang, Seohyun Kim, Jeany Son, Bohyung Han

We present a weakly supervised instance segmentation algorithm based on deep community learning with multiple tasks. This task is formulated as a combination of weakly supervised object detection and semantic segmentation, where individual objects of the same class are identified and segmented separately. We address this problem by designing a unified deep neural network architecture, which has a positive feedback loop of object detection with bounding box regression, instance mask generation, instance segmentation, and feature extraction. Each component of the network makes active interactions with others to improve accuracy, and the end-to-end trainability of our model makes our results more robust and reproducible. The proposed algorithm achieves state-of-the-art performance in the weakly supervised setting without any additional training such as Fast R-CNN and Mask R-CNN on the standard benchmark dataset. The implementation of our algorithm is available on the project webpage: https://cv.snu.ac.kr/research/WSIS_CL.

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Tasks

Image-level Supervised Instance Segmentation Instance Segmentation Object Detection Segmentation Semantic Segmentation Weakly Supervised Object Detection Weakly-supervised instance segmentation object-detection

Results from the paper archive 2025-07-28

Task	Dataset	Model	Metric	Value	Rank at snapshot	Leaderboard	Report
Image-level Supervised Instance Segmentation	PASCAL VOC 2012 val	CL	mAP@0.25	56.6	#10 of 13	Archive leaderboard	report
Image-level Supervised Instance Segmentation	PASCAL VOC 2012 val	CL	mAP@0.5	38.1	#10 of 13	Archive leaderboard	report
Image-level Supervised Instance Segmentation	PASCAL VOC 2012 val	CL	mAP@0.75	12.3	#10 of 13	Archive leaderboard	report
Weakly-supervised instance segmentation	PASCAL VOC 2012 val	WSIS_CL	Average Best Overlap	48.2	#3 of 6	Archive leaderboard	report
Weakly-supervised instance segmentation	PASCAL VOC 2012 val	WSIS_CL	mAP@0.25	56.6	#3 of 6	Archive leaderboard	report
Weakly-supervised instance segmentation	PASCAL VOC 2012 val	WSIS_CL	mAP@0.5	38.1	#3 of 6	Archive leaderboard	report
Weakly-supervised instance segmentation	PASCAL VOC 2012 val	WSIS_CL	mAP@0.75	12.3	#3 of 6	Archive leaderboard	report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Convolution Fast R-CNN Mask R-CNN RPN RoIAlign RoIPool Softmax

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