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arXiv · 2106.08650

Shuffle Transformer with Feature Alignment for Video Face Parsing

Rui Zhang·Yang Han·Zilong Huang·Pei Cheng·Guozhong Luo·Gang Yu·Bin Fu
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Abstract

This is a short technical report introducing the solution of the Team TCParser for Short-video Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 2021. In this paper, we introduce a strong backbone which is cross-window based Shuffle Transformer for presenting accurate face parsing representation. To further obtain the finer segmentation results, especially on the edges, we introduce a Feature Alignment Aggregation (FAA) module. It can effectively relieve the feature misalignment issue caused by multi-resolution feature aggregation. Benefiting from the stronger backbone and better feature aggregation, the proposed method achieves 86.9519% score in the Short-video Face Parsing track of the 3rd Person in Context (PIC) Workshop and Challenge, ranked the first place.

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Rui Zhang, Yang Han, Zilong Huang, Pei Cheng, Guozhong Luo, Gang Yu, Bin Fu. 2021-06-16. Shuffle Transformer with Feature Alignment for Video Face Parsing. https://arxiv.org/abs/2106.08650

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