6 citations · 10 across the 14 of their papers we have counts for
5 papers · 1 filter
Fit Pixels, Get Labels: Meta-learned Implicit Networks for Image Segmentation
Kushal Vyas, Ashok Veeraraghavan, Guha Balakrishnan
Implicit neural representations (INRs) have achieved remarkable successes in learning expressive yet compact signal representations. However, they are not naturally amenable to pre…
COMPASS: Robust Feature Conformal Prediction for Medical Segmentation Metrics
Matt Y. Cheung, Ashok Veeraraghavan, Guha Balakrishnan
In clinical applications, the utility of segmentation models is often based on the accuracy of derived downstream metrics such as organ size, rather than by the pixel-level accurac…
FastAvatar: Instant 3D Gaussian Splatting for Faces from Single Unconstrained Poses
Hao Liang, Zhixuan Ge, Soumendu Majee +4
We present FastAvatar, a fast and robust algorithm for single-image 3D face reconstruction using 3D Gaussian Splatting (3DGS). Given a single input image from an arbitrary pose, Fa…
Post-Hurricane Debris Segmentation Using Fine-Tuned Foundational Vision Models
Kooshan Amini, Yuhao Liu, Jamie Ellen Padgett +2
Timely and accurate detection of hurricane debris is critical for effective disaster response and community resilience. While post-disaster aerial imagery is readily available, rob…
When are Diffusion Priors Helpful in Sparse Reconstruction? A Study with Sparse-view CT
Matt Y. Cheung, Sophia Zorek, Tucker J. Netherton +4
Diffusion models demonstrate state-of-the-art performance on image generation, and are gaining traction for sparse medical image reconstruction tasks. However, compared to classica…