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Home > Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 > No. 2: AAAI-22 Technical Tracks 2

CPRAL: Collaborative Panoptic-Regional Active Learning for Semantic Segmentation

February 1, 2023

Authors

Yu Qiao

Dalian University of Technology


Jincheng Zhu

Dalian University of Technology


Chengjiang Long

JD Finance America Corporation


Zeyao Zhang

Dalian University of Technology


Yuxin Wang

Dalian University of Technology


Zhenjun Du

SIASUN Robot & Automation CO.,Ltd


Xin Yang

Dalian University of Technology


Proceedings:

No. 2: AAAI-22 Technical Tracks 2

Volume

Issue:

Proceedings of the AAAI Conference on Artificial Intelligence, 36

Track:

AAAI Technical Track on Computer Vision II

Downloads:

Download PDF

Abstract:

Acquiring the most representative examples via active learning (AL) can benefit many data-dependent computer vision tasks by minimizing efforts of image-level or pixel-wise annotations. In this paper, we propose a novel Collaborative Panoptic-Regional Active Learning framework (CPRAL) to address the semantic segmentation task. For a small batch of images initially sampled with pixel-wise annotations, we employ panoptic information to initially select unlabeled samples. Considering the class imbalance in the segmentation dataset, we import a Regional Gaussian Attention module (RGA) to achieve semantics-biased selection. The subset is highlighted by vote entropy and then attended by Gaussian kernels to maximize the biased regions. We also propose a Contextual Labels Extension (CLE) to boost regional annotations with contextual attention guidance. With the collaboration of semantics-agnostic panoptic matching and region-biased selection and extension, our CPRAL can strike a balance between labeling efforts and performance and compromise the semantics distribution. We perform extensive experiments on Cityscapes and BDD10K datasets and show that CPRAL outperforms the cutting-edge methods with impressive results and less labeling proportion.

DOI:

10.1609/aaai.v36i2.20107


AAAI

Proceedings of the AAAI Conference on Artificial Intelligence, 36



Topics: AAAI

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