3 papers
cs.LG2026
Geometry Preserving Loss Functions Promote Improved Adaptation of Blackbox Generative Model
Sinjini Mitra, Constantine Kyriakakis, Shenyuan Liang +2
Adaptation of blackbox generative models has been widely studied recently through the exploration of several methods including generator fine-tuning, latent space searches, leverag…
cs.CV2025
Investigating Image Manifolds of 3D Objects: Learning, Shape Analysis, and Comparisons
Benjamin Beaudett, Shenyuan Liang, Anuj Srivastava
Despite high-dimensionality of images, the sets of images of 3D objects have long been hypothesized to form low-dimensional manifolds. What is the nature of such manifolds? How do…
cs.CV2023
Shape-Graph Matching Network (SGM-net): Registration for Statistical Shape Analysis
Shenyuan Liang, Mauricio Pamplona Segundo, Sathyanarayanan N. Aakur +2
This paper focuses on the statistical analysis of shapes of data objects called shape graphs, a set of nodes connected by articulated curves with arbitrary shapes. A critical need…