134 citations · 315 across the 7 of their papers we have counts for
7 papers
Unsupervised Coordinate-Based Video Denoising
Mary Damilola Aiyetigbo, Dineshchandar Ravichandran, Reda Chalhoub +2
In this paper, we introduce a novel unsupervised video denoising deep learning approach that can help to mitigate data scarcity issues and shows robustness against different noise…
Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists
Albert Swiecicki, Nianyi Li, Jonathan O'Donnell +5
A fully-automated deep learning algorithm matched performance of radiologists in assessment of knee osteoarthritis severity in radiographs using the Kellgren-Lawrence grading syste…
Mutual Adaptive Reasoning for Monocular 3D Multi-Person Pose Estimation
Juze Zhang, Jingya Wang, Ye Shi +3
Inter-person occlusion and depth ambiguity make estimating the 3D poses of monocular multiple persons as camera-centric coordinates a challenging problem. Typical top-down framewor…
NIMBLE: A Non-rigid Hand Model with Bones and Muscles
Yuwei Li, Longwen Zhang, Zesong Qiu +6
Emerging Metaverse applications demand reliable, accurate, and photorealistic reproductions of human hands to perform sophisticated operations as if in the physical world. While re…
Detection of masses and architectural distortions in digital breast tomosynthesis: a publicly available dataset of 5,060 patients and a deep learning model
Mateusz Buda, Ashirbani Saha, Ruth Walsh +5
Breast cancer screening is one of the most common radiological tasks with over 39 million exams performed each year. While breast cancer screening has been one of the most studied…
Deep Surface Light Fields
Anpei Chen, Minye Wu, Yingliang Zhang +4
A surface light field represents the radiance of rays originating from any points on the surface in any directions. Traditional approaches require ultra-dense sampling to ensure th…
Personalized Saliency and its Prediction
Yanyu Xu, Shenghua Gao, Junru Wu +2
Nearly all existing visual saliency models by far have focused on predicting a universal saliency map across all observers. Yet psychology studies suggest that visual attention of…