29 citations · 34 across the 15 of their papers we have counts for
4 papers · 2 filters
A Two-Stage Progressive Pre-training using Multi-Modal Contrastive Masked Autoencoders
Muhammad Abdullah Jamal, Omid Mohareri
In this paper, we propose a new progressive pre-training method for image understanding tasks which leverages RGB-D datasets. The method utilizes Multi-Modal Contrastive Masked Aut…
VidLPRO: A eo-anguage re-training Framework for botic and Laparoscopic Surgery
Mohammadmahdi Honarmand, Muhammad Abdullah Jamal, Omid Mohareri
We introduce VidLPRO, a novel video-language (VL) pre-training framework designed specifically for robotic and laparoscopic surgery. While existing surgical VL models primarily rel…
Rethinking RGB-D Fusion for Semantic Segmentation in Surgical Datasets
Muhammad Abdullah Jamal, Omid Mohareri
Surgical scene understanding is a key technical component for enabling intelligent and context aware systems that can transform various aspects of surgical interventions. In this w…
AdaEmbed: Semi-supervised Domain Adaptation in the Embedding Space
Ali Mottaghi, Mohammad Abdullah Jamal, Serena Yeung +1
Semi-supervised domain adaptation (SSDA) presents a critical hurdle in computer vision, especially given the frequent scarcity of labeled data in real-world settings. This scarcity…