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Shape Adaptor: A Learnable Resizing Module
v1v2 (latest)

Shape Adaptor: A Learnable Resizing Module

3 August 2020
Shikun Liu
Zhe Lin
Yilin Wang
Jianming Zhang
Federico Perazzi
Edward Johns
ArXiv (abs)PDFHTMLGithub (73★)

Papers citing "Shape Adaptor: A Learnable Resizing Module"

4 / 4 papers shown
Title
Balanced Mixture of SuperNets for Learning the CNN Pooling Architecture
Balanced Mixture of SuperNets for Learning the CNN Pooling Architecture
Mehraveh Javan
Matthew Toews
M. Pedersoli
239
1
0
21 Jun 2023
Scale-Space Hypernetworks for Efficient Biomedical Imaging
Scale-Space Hypernetworks for Efficient Biomedical Imaging
Jose Javier Gonzalez Ortiz
John Guttag
Adrian Dalca
146
0
0
11 Apr 2023
Receptive Field Refinement for Convolutional Neural Networks Reliably
  Improves Predictive Performance
Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performance
Mats L. Richter
C. Pal
146
5
0
26 Nov 2022
Efficient Joint-Dimensional Search with Solution Space Regularization
  for Real-Time Semantic Segmentation
Efficient Joint-Dimensional Search with Solution Space Regularization for Real-Time Semantic SegmentationInternational Journal of Computer Vision (IJCV), 2022
Peng Ye
Baopu Li
Tao Chen
Jiayuan Fan
Zhen Mei
Chen-Fu Lin
Chongyan Zuo
Qinghua Chi
Wanli Ouyan
3DV
146
12
0
10 Aug 2022
1