3 citations · 6 across the 5 of their papers we have counts for
4 papers · 1 filter
SpotlessSplats: Ignoring Distractors in 3D Gaussian Splatting
Sara Sabour, Lily Goli, George Kopanas +6
3D Gaussian Splatting (3DGS) is a promising technique for 3D reconstruction, offering efficient training and rendering speeds, making it suitable for real-time applications.However…
ITI-GEN: Inclusive Text-to-Image Generation
Cheng Zhang, Xuanbai Chen, Siqi Chai +4
Text-to-image generative models often reflect the biases of the training data, leading to unequal representations of underrepresented groups. This study investigates inclusive text…
TEGLO: High Fidelity Canonical Texture Mapping from Single-View Images
Vishal Vinod, Tanmay Shah, Dmitry Lagun
Recent work in Neural Fields (NFs) learn 3D representations from class-specific single view image collections. However, they are unable to reconstruct the input data preserving hig…
Solving Inverse Problems with NerfGANs
Giannis Daras, Wen-Sheng Chu, Abhishek Kumar +2
We introduce a novel framework for solving inverse problems using NeRF-style generative models. We are interested in the problem of 3-D scene reconstruction given a single 2-D imag…