1 citations · 2 across the 5 of their papers we have counts for
5 papers
Systematic Evaluation of Large Vision-Language Models for Surgical Artificial Intelligence
Anita Rau, Mark Endo, Josiah Aklilu +6
Large Vision-Language Models offer a new paradigm for AI-driven image understanding, enabling models to perform tasks without task-specific training. This flexibility holds particu…
A Large-Scale Vision-Language Dataset Derived from Open Scientific Literature to Advance Biomedical Generalist AI
Alejandro Lozano, Min Woo Sun, James Burgess +16
Despite the excitement behind biomedical artificial intelligence (AI), access to high-quality, diverse, and large-scale data - the foundation for modern AI systems - is still a bot…
Video Action Differencing
James Burgess, Xiaohan Wang, Yuhui Zhang +5
How do two individuals differ when performing the same action? In this work, we introduce Video Action Differencing (VidDiff), the novel task of identifying subtle differences betw…
BIOMEDICA: An Open Biomedical Image-Caption Archive, Dataset, and Vision-Language Models Derived from Scientific Literature
Alejandro Lozano, Min Woo Sun, James Burgess +13
The development of vision-language models (VLMs) is driven by large-scale and diverse multimodal datasets. However, progress toward generalist biomedical VLMs is limited by the lac…
Depth-guided NeRF Training via Earth Mover's Distance
Anita Rau, Josiah Aklilu, F. Christopher Holsinger +1
Neural Radiance Fields (NeRFs) are trained to minimize the rendering loss of predicted viewpoints. However, the photometric loss often does not provide enough information to disamb…