collaborators

6 papers

cs.CV2026

UnSCAR: Universal, Scalable, Controllable, and Adaptable Image Restoration

Debabrata Mandal, Soumitri Chattopadhyay, Yujie Wang +2

Universal image restoration aims to recover clean images from arbitrary real-world degradations using a single inference model. Despite significant progress, existing all-in-one re…

eess.IV2026

On The Robustness of Foundational 3D Medical Image Segmentation Models Against Imprecise Visual Prompts

Soumitri Chattopadhyay, Basar Demir, Marc Niethammer

While 3D foundational models have shown promise for promptable segmentation of medical volumes, their robustness to imprecise prompts remains under-explored. In this work, we aim t…

cs.CV2025

NoTeS-Bank: Benchmarking Neural Transcription and Search for Scientific Notes Understanding

Aniket Pal, Sanket Biswas, Alloy Das +6

Understanding and reasoning over academic handwritten notes remains a challenge in document AI, particularly for mathematical equations, diagrams, and scientific notations. Existin…

cs.CV2025

Zero-shot Domain Generalization of Foundational Models for 3D Medical Image Segmentation: An Experimental Study

Soumitri Chattopadhyay, Basar Demir, Marc Niethammer

Domain shift, caused by variations in imaging modalities and acquisition protocols, limits model generalization in medical image segmentation. While foundation models (FMs) trained…

eess.IV2025

Downstream Analysis of Foundational Medical Vision Models for Disease Progression

Basar Demir, Soumitri Chattopadhyay, Thomas Hastings Greer +2

Medical vision foundational models are used for a wide variety of tasks, including medical image segmentation and registration. This work evaluates the ability of these models to p…

cs.CV2025

UniCoRN: Latent Diffusion-based Unified Controllable Image Restoration Network across Multiple Degradations

Debabrata Mandal, Soumitri Chattopadhyay, Guansen Tong +1

Image restoration is essential for enhancing degraded images across computer vision tasks. However, most existing methods address only a single type of degradation (e.g., blur, noi…