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Unifying Feature and Cost Aggregation with Transformers for Semantic and
  Visual Correspondence

Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence

17 March 2024
Sung‐Jin Hong
Seokju Cho
Seungryong Kim
Stephen Lin
    ViT
ArXivPDFHTML

Papers citing "Unifying Feature and Cost Aggregation with Transformers for Semantic and Visual Correspondence"

5 / 5 papers shown
Title
TransforMatcher: Match-to-Match Attention for Semantic Correspondence
TransforMatcher: Match-to-Match Attention for Semantic Correspondence
Seungwook Kim
Juhong Min
Minsu Cho
ViT
35
23
0
23 May 2022
DKM: Dense Kernelized Feature Matching for Geometry Estimation
DKM: Dense Kernelized Feature Matching for Geometry Estimation
Johan Edstedt
Ioannis Athanasiadis
Mårten Wadenbäck
M. Felsberg
3DV
MDE
27
114
0
01 Feb 2022
PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
Prune Truong
Martin Danelljan
Radu Timofte
Luc Van Gool
18
82
0
28 Sep 2021
Learning Accurate Dense Correspondences and When to Trust Them
Learning Accurate Dense Correspondences and When to Trust Them
Prune Truong
Martin Danelljan
Luc Van Gool
Radu Timofte
3DH
3DPC
64
125
0
05 Jan 2021
Semantic Understanding of Scenes through the ADE20K Dataset
Semantic Understanding of Scenes through the ADE20K Dataset
Bolei Zhou
Hang Zhao
Xavier Puig
Tete Xiao
Sanja Fidler
Adela Barriuso
Antonio Torralba
SSeg
243
1,817
0
18 Aug 2016
1