4 papers
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs
Harini Suresh, Kathleen M. Lewis, John V. Guttag +1
Interpretability methods aim to help users build trust in and understand the capabilities of machine learning models. However, existing approaches often rely on abstract, complex v…
TryOnGAN: Body-Aware Try-On via Layered Interpolation
Kathleen M Lewis, Srivatsan Varadharajan, Ira Kemelmacher-Shlizerman
Given a pair of images-target person and garment on another person-we automatically generate the target person in the given garment. Previous methods mostly focused on texture tran…
Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings
Amy Zhao, Guha Balakrishnan, Kathleen M. Lewis +3
We introduce a new video synthesis task: synthesizing time lapse videos depicting how a given painting might have been created. Artists paint using unique combinations of brushes,…
Fast Learning-based Registration of Sparse 3D Clinical Images
Kathleen M. Lewis, Natalia S. Rost, John Guttag +1
We introduce SparseVM, a method that registers clinical-quality 3D MR scans both faster and more accurately than previously possible. Deformable alignment, or registration, of clin…