activity
20192025
most citedRevisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers

5 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2025

Investigating Robot Control Policy Learning for Autonomous X-ray-guided Spine Procedures

Florence Klitzner, Blanca Inigo, Benjamin D. Killeen +4

Imitation learning-based robot control policies are enjoying renewed interest in video-based robotics. However, it remains unclear whether this approach applies to X-ray-guided pro…

cs.CV2025

Egosurg: Arbitrary view synthesis for egocentric replay of operating room workflows from ambient cameras

Han Zhang, Lalithkumar Seenivasan, Jose L. Porras +10

Observing surgical practice has historically relied on fixed vantage points or recollections, leaving the egocentric perspectives that shape clinical decisions undocumented. Ambien…

cs.LG2025★ 2 cited

Detecting Dataset Bias in Medical AI: A Generalized and Modality-Agnostic Auditing Framework

Nathan Drenkow, Mitchell Pavlak, Keith Harrigian +5

Artificial Intelligence (AI) is now firmly at the center of evidence-based medicine. Despite many success stories that edge the path of AI's rise in healthcare, there are comparabl…

cs.CV2023

MoViT: Memorizing Vision Transformers for Medical Image Analysis

Yiqing Shen, Pengfei Guo, Jingpu Wu +5

The synergy of long-range dependencies from transformers and local representations of image content from convolutional neural networks (CNNs) has led to advanced architectures and…

cs.CV2020★ 5 cited

Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers

Zhaoshuo Li, Xingtong Liu, Nathan Drenkow +4

Stereo depth estimation relies on optimal correspondence matching between pixels on epipolar lines in the left and right images to infer depth. In this work, we revisit the problem…

cs.CV2019

LumiPath -- Towards Real-time Physically-based Rendering on Embedded Devices

Laura Fink, Sing Chun Lee, Jie Ying Wu +6

With the increasing computational power of today's workstations, real-time physically-based rendering is within reach, rapidly gaining attention across a variety of domains. These…