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20212025
most citedSelf-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

106 citations · 122 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2025

ReservoirTTA: Prolonged Test-time Adaptation for Evolving and Recurring Domains

Guillaume Vray, Devavrat Tomar, Xufeng Gao +3

This paper introduces ReservoirTTA, a novel plug-in framework designed for prolonged test-time adaptation (TTA) in scenarios where the test domain continuously shifts over time, in…

cs.CV2025

Slide-Level Prompt Learning with Vision Language Models for Few-Shot Multiple Instance Learning in Histopathology

Devavrat Tomar, Guillaume Vray, Dwarikanath Mahapatra +3

In this paper, we address the challenge of few-shot classification in histopathology whole slide images (WSIs) by utilizing foundational vision-language models (VLMs) and slide-lev…

cs.CV2024

Un-Mixing Test-Time Normalization Statistics: Combatting Label Temporal Correlation

Devavrat Tomar, Guillaume Vray, Jean-Philippe Thiran +1

Recent test-time adaptation methods heavily rely on nuanced adjustments of batch normalization (BN) parameters. However, one critical assumption often goes overlooked: that of inde…

cs.CV2023★ 15 cited

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

Guillaume Vray, Devavrat Tomar, Jean-Philippe Thiran +1

Developing computational pathology models is essential for reducing manual tissue typing from whole slide images, transferring knowledge from the source domain to an unlabeled, shi…

cs.CV2023

TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation

Devavrat Tomar, Guillaume Vray, Behzad Bozorgtabar +1

Most recent test-time adaptation methods focus on only classification tasks, use specialized network architectures, destroy model calibration or rely on lightweight information fro…

cs.CV2021

Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

Devavrat Tomar, Behzad Bozorgtabar, Manana Lortkipanidze +3

In medical image segmentation, supervised deep networks' success comes at the cost of requiring abundant labeled data. While asking domain experts to annotate only one or a few of…

cs.CV2021★ 106 cited

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

Devavrat Tomar, Manana Lortkipanidze, Guillaume Vray +2

Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the traini…

eess.IV2021★ 1 cited

Content-Preserving Unpaired Translation from Simulated to Realistic Ultrasound Images

Devavrat Tomar, Lin Zhang, Tiziano Portenier +1

Interactive simulation of ultrasound imaging greatly facilitates sonography training. Although ray-tracing based methods have shown promising results, obtaining realistic images re…