collaborators

5 papers

cs.LG2026

A Markovian View of Iterative-Feedback Loops in Image Generative Models: Neural Resonance and Model Collapse

Vibhas Kumar Vats, David J. Crandall, Samuel Goree

AI training datasets will inevitably contain AI-generated examples, leading to ``feedback'' in which the output of one model impacts the training of another. It is known that such…

cs.CV2025

Blending 3D Geometry and Machine Learning for Multi-View Stereopsis

Vibhas Vats, Md. Alimoor Reza, David Crandall +1

Traditional multi-view stereo (MVS) methods primarily depend on photometric and geometric consistency constraints. In contrast, modern learning-based algorithms often rely on the p…

cs.LG2025

Geospatial Diffusion for Land Cover Imperviousness Change Forecasting

Debvrat Varshney, Vibhas Vats, Bhartendu Pandey +2

Land cover, both present and future, has a significant effect on several important Earth system processes. For example, impervious surfaces heat up and speed up surface water runof…

cs.CV2025

GC-MVSNet: Multi-View, Multi-Scale, Geometrically-Consistent Multi-View Stereo

Vibhas K. Vats, Sripad Joshi, David J. Crandall +2

Traditional multi-view stereo (MVS) methods rely heavily on photometric and geometric consistency constraints, but newer machine learning-based MVS methods check geometric consiste…

cs.CV2025

Geometric Constraints in Deep Learning Frameworks: A Survey

Vibhas K Vats, David J Crandall

Stereophotogrammetry is an established technique for scene understanding. Its origins go back to at least the 1800s when people first started to investigate using photographs to me…