2 citations · 3 across the 16 of their papers we have counts for
8 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…
GIQ: Benchmarking 3D Geometric Reasoning of Vision Foundation Models with Simulated and Real Polyhedra
Mateusz Michalkiewicz, Anekha Sokhal, Tadeusz Michalkiewicz +4
Modern monocular 3D reconstruction methods and vision-language models (VLMs) demonstrate impressive results on standard benchmarks, yet recent works cast doubt on their true unders…
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…
TranSplat: Instant Object Relighting in Gaussian Splatting via Spherical Harmonic Radiance Transfer
Boyang Tony Yu, Yanlin Jin, Yun He +3
We present TranSplat, a method for instant, accurate object relighting within the Gaussian Splatting (GS) framework. Rather than relying on costly inverse rendering routines, we pr…
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…
Bias for Action: Video Implicit Neural Representations with Bias Modulation
Alper Kayabasi, Anil Kumar Vadathya, Guha Balakrishnan +1
We propose a new continuous video modeling framework based on implicit neural representations (INRs) called ActINR. At the core of our approach is the observation that INRs can be…