2 citations · 2 across the 1 of their papers we have counts for
7 papers
ShaRF: Shape-conditioned Radiance Fields from a Single View
Konstantinos Rematas, Ricardo Martin-Brualla, Vittorio Ferrari
We present a method for estimating neural scenes representations of objects given only a single image. The core of our method is the estimation of a geometric scaffold for the obje…
From Points to Multi-Object 3D Reconstruction
Francis Engelmann, Konstantinos Rematas, Bastian Leibe +1
We propose a method to detect and reconstruct multiple 3D objects from a single RGB image. The key idea is to optimize for detection, alignment and shape jointly over all objects i…
Reconstructing NBA Players
Luyang Zhu, Konstantinos Rematas, Brian Curless +2
Great progress has been made in 3D body pose and shape estimation from a single photo. Yet, state-of-the-art results still suffer from errors due to challenging body poses, modelin…
Neural Voxel Renderer: Learning an Accurate and Controllable Rendering Tool
Konstantinos Rematas, Vittorio Ferrari
We present a neural rendering framework that maps a voxelized scene into a high quality image. Highly-textured objects and scene element interactions are realistically rendered by…
PhotoShape: Photorealistic Materials for Large-Scale Shape Collections
Keunhong Park, Konstantinos Rematas, Ali Farhadi +1
Existing online 3D shape repositories contain thousands of 3D models but lack photorealistic appearance. We present an approach to automatically assign high-quality, realistic appe…
Soccer on Your Tabletop
Konstantinos Rematas, Ira Kemelmacher-Shlizerman, Brian Curless +1
We present a system that transforms a monocular video of a soccer game into a moving 3D reconstruction, in which the players and field can be rendered interactively with a 3D viewe…