10 citations · 10 across the 5 of their papers we have counts for
6 papers
Aligning Misaligned Benchmarks for Single-View Novel View Synthesis
Yang-Che Tseng, Erqun Dong, Jeong-gi Kwak +5
While single-view novel view synthesis methods have been dramatically enhanced recently, how to quantify their performance has yet to be standardized. In this work, we demonstrate…
3D Gaussian Splatting as Markov Chain Monte Carlo
Shakiba Kheradmand, Daniel Rebain, Gopal Sharma +6
While 3D Gaussian Splatting has recently become popular for neural rendering, current methods rely on carefully engineered cloning and splitting strategies for placing Gaussians, w…
PointNeRF++: A multi-scale, point-based Neural Radiance Field
Weiwei Sun, Eduard Trulls, Yang-Che Tseng +4
Point clouds offer an attractive source of information to complement images in neural scene representations, especially when few images are available. Neural rendering methods base…
Volumetric Rendering with Baked Quadrature Fields
Gopal Sharma, Daniel Rebain, Kwang Moo Yi +1
We propose a novel Neural Radiance Field (NeRF) representation for non-opaque scenes that enables fast inference by utilizing textured polygons. Despite the high-quality novel view…
Unsupervised Keypoints from Pretrained Diffusion Models
Eric Hedlin, Gopal Sharma, Shweta Mahajan +5
Unsupervised learning of keypoints and landmarks has seen significant progress with the help of modern neural network architectures, but performance is yet to match the supervised…
Accelerating Neural Field Training via Soft Mining
Shakiba Kheradmand, Daniel Rebain, Gopal Sharma +4
We present an approach to accelerate Neural Field training by efficiently selecting sampling locations. While Neural Fields have recently become popular, it is often trained by uni…