488 citations · 673 across the 15 of their papers we have counts for
3 papers · 2 filters
Hypersim: A Photorealistic Synthetic Dataset for Holistic Indoor Scene Understanding
Mike Roberts, Jason Ramapuram, Anurag Ranjan +5
For many fundamental scene understanding tasks, it is difficult or impossible to obtain per-pixel ground truth labels from real images. We address this challenge by introducing Hyp…
On the generalization of learning-based 3D reconstruction
Miguel Angel Bautista, Walter Talbott, Shuangfei Zhai +2
State-of-the-art learning-based monocular 3D reconstruction methods learn priors over object categories on the training set, and as a result struggle to achieve reasonable generali…
Equivariant Neural Rendering
Emilien Dupont, Miguel Angel Bautista, Alex Colburn +4
We propose a framework for learning neural scene representations directly from images, without 3D supervision. Our key insight is that 3D structure can be imposed by ensuring that…