Search Results for author: Devavrat Tomar

Found 6 papers, 5 papers with code

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

2 code implementations10 Jul 2023 Guillaume Vray, Devavrat Tomar, Jean-Philippe Thiran, Behzad Bozorgtabar

Developing computational pathology models is essential for reducing manual tissue typing from whole slide images, transferring knowledge from the source domain to an unlabeled, shifted target domain, and identifying unseen categories.

Data Augmentation Domain Adaptation +2

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

1 code implementation CVPR 2023 Devavrat Tomar, Guillaume Vray, Behzad Bozorgtabar, Jean-Philippe Thiran

Most recent test-time adaptation methods focus on only classification tasks, use specialized network architectures, destroy model calibration or rely on lightweight information from the source domain.

Knowledge Distillation Self-Learning +1

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

1 code implementation5 Oct 2021 Devavrat Tomar, Behzad Bozorgtabar, Manana Lortkipanidze, Guillaume Vray, Mohammad Saeed Rad, Jean-Philippe Thiran

Motivated by atlas-based segmentation, we propose a novel volumetric self-supervised learning for data augmentation capable of synthesizing volumetric image-segmentation pairs via learning transformations from a single labeled atlas to the unlabeled data.

Data Augmentation Image Segmentation +7

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

1 code implementation5 Mar 2021 Devavrat Tomar, Manana Lortkipanidze, Guillaume Vray, Behzad Bozorgtabar, Jean-Philippe Thiran

We present a novel approach for image-to-image translation in medical images, capable of supervised or unsupervised (unpaired image data) setups.

Domain Adaptation Image-to-Image Translation +1

Cannot find the paper you are looking for? You can Submit a new open access paper.