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20212025
most citedPUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splatting

2 citations · 2 across the 6 of their papers we have counts for

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cs.CV2025

SplatSuRe: Selective Super-Resolution for Multi-view Consistent 3D Gaussian Splatting

Pranav Asthana, Alex Hanson, Allen Tu +3

3D Gaussian Splatting (3DGS) enables high-quality novel view synthesis, motivating interest in generating higher-resolution renders than those available during training. A natural…

cs.CV2024

Speedy-Splat: Fast 3D Gaussian Splatting with Sparse Pixels and Sparse Primitives

Alex Hanson, Allen Tu, Geng Lin +3

3D Gaussian Splatting (3D-GS) is a recent 3D scene reconstruction technique that enables real-time rendering of novel views by modeling scenes as parametric point clouds of differe…

cs.CV2024★ 2 cited

PUP 3D-GS: Principled Uncertainty Pruning for 3D Gaussian Splatting

Alex Hanson, Allen Tu, Vasu Singla +3

Recent advances in novel view synthesis have enabled real-time rendering speeds with high reconstruction accuracy. 3D Gaussian Splatting (3D-GS), a foundational point-based paramet…

cs.CV2021

Rethinking Common Assumptions to Mitigate Racial Bias in Face Recognition Datasets

Matthew Gwilliam, Srinidhi Hegde, Lade Tinubu +1

Many existing works have made great strides towards reducing racial bias in face recognition. However, most of these methods attempt to rectify bias that manifests in models during…

cs.CV2021

SVMax: A Feature Embedding Regularizer

Ahmed Taha, Alex Hanson, Abhinav Shrivastava +1

A neural network regularizer (e.g., weight decay) boosts performance by explicitly penalizing the complexity of a network. In this paper, we penalize inferior network activations -…