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researcher

Xiaohui Xie

10 papers hereh-index 13845 citations18 works total

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

author position
  • middle author4
  • last author5

Across the 9 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CV7
  • cs.AI1
  • cs.LG1
  • eess.IV1
same name
  • Xiaohui Xie — 38 papers, h 35
  • Xiaohui Xie — 13 papers, h 16
  • Xiaohui Xie — 13 papers, h 44
  • Xiaohui Xie — 12 papers, h 5
  • Xiaohui Xie — 8 papers, h 3
  • Xiaohui Xie — 7 papers, 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

activity
20182022
most citedTransFusion: Cross-view Fusion with Transformer for 3D Human Pose Estimation

36 citations · 91 across the 10 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022

Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training

Zhenglun Kong, Haoyu Ma, Geng Yuan +12

Vision transformers (ViTs) have recently obtained success in many applications, but their intensive computation and heavy memory usage at both training and inference time limit the…

cs.CV2022★ 2 cited

PPT: token-Pruned Pose Transformer for monocular and multi-view human pose estimation

Haoyu Ma, Zhe Wang, Yifei Chen +6

Recently, the vision transformer and its variants have played an increasingly important role in both monocular and multi-view human pose estimation. Considering image patches as to…

cs.CV2022

Medical Image Registration via Neural Fields

Shanlin Sun, Kun Han, Chenyu You +8

Image registration is an essential step in many medical image analysis tasks. Traditional methods for image registration are primarily optimization-driven, finding the optimal defo…

cs.CV2022★ 2 cited

Topology-Preserving Shape Reconstruction and Registration via Neural Diffeomorphic Flow

Shanlin Sun, Kun Han, Deying Kong +3

Deep Implicit Functions (DIFs) represent 3D geometry with continuous signed distance functions learned through deep neural nets. Recently DIFs-based methods have been proposed to h…

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