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3rd Place Solution for Short-video Face Parsing Challenge

arXiv 2106.07409 ↗First posted 14 Jun 2021cs.CVcited by 0

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Abstract (arXiv)

This is a short technical report introducing the solution of Team Rat for Short-video Parsing Face Parsing Track of The 3rd Person in Context (PIC) Workshop and Challenge at CVPR 2021. In this report, we propose an Edge-Aware Network (EANet) that uses edge information to refine the segmentation edge. To further obtain the finer edge results, we introduce edge attention loss that only compute cross entropy on the edges, it can effectively reduce the classification error around edge and get more smooth boundary. Benefiting from the edge information and edge attention loss, the proposed EANet achieves 86.16% accuracy in the Short-video Face Parsing track of the 3rd Person in Context (PIC) Workshop and Challenge, ranked the third place.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 15 of its 21 references that are in the map. First posted on arXiv 14 Jun 2021.

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References · 15

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3 more
  1. 2018Devil in the Details: Towards Accurate Single and Multiple Human Parsingcited by 64
  2. 2019Face Parsing with RoI Tanh-Warpingcited by 33
  3. 2020AinnoSeg: Panoramic Segmentation with High Perfomancecited by 2

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