Close the Loop: A Unified Bottom-Up and Top-Down Paradigm for Joint Image Deraining and Segmentation
نویسندگان
چکیده
In this work, we focus on a very practical problem: image segmentation under rain conditions. Image deraining is classic low-level restoration task, while typical high-level understanding task. Most of the existing methods intuitively employ bottom-up paradigm by taking as preprocessing step for subsequent segmentation. However, our statistical analysis indicates that not only would benefit (bottom-up), but also further improve performance (top-down) in turn. This motivates us to solve rainy task within novel top-down and unified paradigm, which two sub-tasks are alternatively performed collaborated with each other. Specifically, procedure yields both clearer images rain-robust features from feature domains, so ease ambiguity caused streaks. The adopts semantics adaptively guide different contents via multi-path semantic attentive module (SAM). Thus could boost other cooperatively progressively. Extensive experiments ablations demonstrate proposed method outperforms state-of-the-art
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ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2022
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v36i2.20033