Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales

Terms and Conditions

Twitter GitHub LinkedIn Bluesky Youtube

© 2026 ResearchTrend.AI, All rights reserved.

Home
Papers
2210.04508
Cited By

Scale Equivariant U-Net

Scale Equivariant U-Net

British Machine Vision Conference (BMVC), 2022

10 October 2022

Mateus Sangalli

Santiago Velasco-Forero

ArXiv (abs)PDF HTML

Papers citing "Scale Equivariant U-Net"

7 / 7 papers shown

Hybrid Lie semi-group and cascade structures for the generalized Gaussian derivative model for visual receptive fields

Hybrid Lie semi-group and cascade structures for the generalized Gaussian derivative model for visual receptive fields

92

1

0

19 Sep 2025

Modelling and analysis of the 8 filters from the "master key filters hypothesis" for depthwise-separable deep networks in relation to idealized receptive fields based on scale-space theory

Modelling and analysis of the 8 filters from the "master key filters hypothesis" for depthwise-separable deep networks in relation to idealized receptive fields based on scale-space theory

Peyman M. Kiasari

120

1

0

16 Sep 2025

Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations

Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variationsJournal of Mathematical Imaging and Vision (JMIV), 2024

Andrzej Perzanowski

439

4

0

17 Sep 2024

HyperSpace: Hypernetworks for spacing-adaptive image segmentation

HyperSpace: Hypernetworks for spacing-adaptive image segmentation

Maximilian Pietsch

Raphael Prevost

223

6

0

04 Jul 2024

Approximation properties relative to continuous scale space for hybrid discretizations of Gaussian derivative operators

Approximation properties relative to continuous scale space for hybrid discretizations of Gaussian derivative operatorsFrontiers in Signal Processing (FSP), 2024

304

5

0

08 May 2024

Unified theory for joint covariance properties under geometric image
transformations for spatio-temporal receptive fields according to the
generalized Gaussian derivative model for visual receptive fields

Unified theory for joint covariance properties under geometric image transformations for spatio-temporal receptive fields according to the generalized Gaussian derivative model for visual receptive fields

399

12

0

17 Nov 2023

What Affects Learned Equivariance in Deep Image Recognition Models?

What Affects Learned Equivariance in Deep Image Recognition Models?

Robert-Jan Bruintjes

319

11

0

05 Apr 2023