Distill-SODA: Distilling Self-Supervised Vision Transformer for
Source-Free Open-Set Domain Adaptation in Computational Pathology

Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology

10 July 2023

Jean-Philippe Thiran

Behzad Bozorgtabar

Papers citing "Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology"

5 / 5 papers shown

Title
Upcycling Models under Domain and Category Shift Sanqing Qu Tianpei Zou Florian Roehrbein Cewu Lu Guang-Sheng Chen Dacheng Tao Changjun Jiang 33 39 0 13 Mar 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,337 0 11 Nov 2021
Open-Set Recognition: a Good Closed-Set Classifier is All You Need? S. Vaze Kai Han Andrea Vedaldi Andrew Zisserman BDL 158 401 0 12 Oct 2021
Intriguing Properties of Vision Transformers Muzammal Naseer Kanchana Ranasinghe Salman Khan Munawar Hayat F. Khan Ming-Hsuan Yang ViT 248 618 0 21 May 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 283 5,723 0 29 Apr 2021