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Bin Fu

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • eess.IV1
same name
  • Bin Fu — 4 papers, h 19
  • Bin Fu — 2 papers
  • Bin Fu — 1 paper
  • Bin Fu — 1 paper
  • Bin Fu — 1 paper, h 2
  • Bin Fu — 1 paper, h 7

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedShuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer

125 citations · 141 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2021★ 2 cited

Fine-grained Identity Preserving Landmark Synthesis for Face Reenactment

Haichao Zhang, Youcheng Ben, Weixi Zhang +3

Recent face reenactment works are limited by the coarse reference landmarks, leading to unsatisfactory identity preserving performance due to the distribution gap between the manip…

cs.CV2021★ 1 cited

Shuffle Transformer with Feature Alignment for Video Face Parsing

Rui Zhang, Yang Han, Zilong Huang +4

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…

cs.CV2021★ 125 cited

Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer

Zilong Huang, Youcheng Ben, Guozhong Luo +3

Very recently, Window-based Transformers, which computed self-attention within non-overlapping local windows, demonstrated promising results on image classification, semantic segme…

eess.IV2021★ 13 cited

Fast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Report

Andrey Ignatov, Grigory Malivenko, David Plowman +35

Depth estimation is an important computer vision problem with many practical applications to mobile devices. While many solutions have been proposed for this task, they are usually…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.