5 citations · 5 across the 1 of their papers we have counts for
3 papers
cs.CV2020★ 5 cited
Segmentation and Recovery of Superquadric Models using Convolutional Neural Networks
Jaka Šircelj, Tim Oblak, Klemen Grm +5
In this paper we address the problem of representing 3D visual data with parameterized volumetric shape primitives. Specifically, we present a (two-stage) approach built around con…
cs.CV2019
Recovery of Superquadrics from Range Images using Deep Learning: A Preliminary Study
Tim Oblak, Klemen Grm, Aleš Jaklič +3
It has been a longstanding goal in computer vision to describe the 3D physical space in terms of parameterized volumetric models that would allow autonomous machines to understand…
cs.CV2018
Face Hallucination Revisited: An Exploratory Study on Dataset Bias
Klemen Grm, Martin Pernuš, Leo Cluzel +3
Contemporary face hallucination (FH) models exhibit considerable ability to reconstruct high-resolution (HR) details from low-resolution (LR) face images. This ability is commonly…