2 citations · 2 across the 6 of their papers we have counts for
6 papers
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…
SpeeDe3DGS: Speedy Deformable 3D Gaussian Splatting with Temporal Pruning and Motion Grouping
Allen Tu, Haiyang Ying, Alex Hanson +3
Dynamic extensions of 3D Gaussian Splatting (3DGS) achieve high-quality reconstructions through neural motion fields, but per-Gaussian neural inference makes these models computati…
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…
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…
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…
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 -…