Unabridged adjacent modulation for clothing parsing

Dong Zhang, Chengting Zuo, Qianhao Wu, Liyong Fu, Xinguang Xiang

Abstract: Highlights•Based on the encoder-decoder architecture, we propose a block-specific unabridged channel attention mechanism, such that features within each block can be recalibrated.•A top-down adjacent modulation for decoder network is proposed so that the lowlevel features substantially contain abundant semantic contexts.•We demonstrate the effectiveness of UAM-Net via two challenging benchmarks. Results declare that we can achieve a new state-of-the-art on colorful fashion parsing dataset and comparable performance on modified fashion clothing dataset with less computation overhead.