44 citations · 100 across the 20 of their papers we have counts for
3 papers · 1 filter
Synthetic Training for Accurate 3D Human Pose and Shape Estimation in the Wild
Akash Sengupta, Ignas Budvytis, Roberto Cipolla
This paper addresses the problem of monocular 3D human shape and pose estimation from an RGB image. Despite great progress in this field in terms of pose prediction accuracy, state…
A CNN Based Approach for the Near-Field Photometric Stereo Problem
Fotios Logothetis, Ignas Budvytis, Roberto Mecca +1
Reconstructing the 3D shape of an object using several images under different light sources is a very challenging task, especially when realistic assumptions such as light propagat…
PX-NET: Simple and Efficient Pixel-Wise Training of Photometric Stereo Networks
Fotios Logothetis, Ignas Budvytis, Roberto Mecca +1
Retrieving accurate 3D reconstructions of objects from the way they reflect light is a very challenging task in computer vision. Despite more than four decades since the definition…