Key Design Choices in Source-Free Unsupervised Domain Adaptation: An
In-depth Empirical Analysis

Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis

25 February 2024

Andrea Maracani

Raffaello Camoriano

Elisa Maiettini

Lorenzo Rosasco

Lorenzo Natale

Papers citing "Key Design Choices in Source-Free Unsupervised Domain Adaptation: An In-depth Empirical Analysis"

8 / 8 papers shown

Title
Source-Free Unsupervised Domain Adaptation: A Survey Yuqi Fang P. Yap W. Lin Hongtu Zhu Mingxia Liu 128 89 0 31 Dec 2022
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,412 0 11 Nov 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 303 5,761 0 29 Apr 2021
High-Performance Large-Scale Image Recognition Without Normalization Andrew Brock Soham De Samuel L. Smith Karen Simonyan VLM 223 512 0 11 Feb 2021
Improved Baselines with Momentum Contrastive Learning Xinlei Chen Haoqi Fan Ross B. Girshick Kaiming He SSL 238 3,367 0 09 Mar 2020
Impact of ImageNet Model Selection on Domain Adaptation Youshan Zhang Brian D. Davison FAtt OOD VLM 39 34 0 06 Feb 2020
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 149 9,316 0 28 May 2015
Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour M. Mohri Afshin Rostamizadeh 179 788 0 19 Feb 2009