1 code implementation • European Conference on Computer Vision 2022 • John Lambert, Yuguang Li, Ivaylo Boyadzhiev, Lambert Wixson, Manjunath Narayana, Will Hutchcroft, James Hays, Frank Dellaert, Sing Bing Kang
Once the room poses are computed, room layouts are inferred using HorizonNet, and the floorplan is constructed by stitching the most confident layout boundaries.
no code implementations • 26 Apr 2023 • Negar Nejatishahidin, Will Hutchcroft, Manjunath Narayana, Ivaylo Boyadzhiev, Yuguang Li, Naji Khosravan, Jana Kosecka, Sing Bing Kang
In this paper, we address the problem of wide-baseline camera pose estimation from a group of 360$^\circ$ panoramas under upright-camera assumption.
1 code implementation • CVPR 2022 • Zhixiang Min, Naji Khosravan, Zachary Bessinger, Manjunath Narayana, Sing Bing Kang, Enrique Dunn, Ivaylo Boyadzhiev
LASER introduces the concept of latent space rendering, where 2D pose hypotheses on the floor map are directly rendered into a geometrically-structured latent space by aggregating viewing ray features.
no code implementations • 17 Oct 2020 • Manjunath Narayana, Andreas Kolling, Lucio Nardelli, Phil Fong
First, as a robot senses new changes and alters its raw map in successive runs, the semantics must be updated appropriately.
no code implementations • 5 Nov 2015 • Manjunath Narayana, Allen Hanson, Erik Learned-Miller
In particular, it is essential to have a background likelihood, a foreground likelihood, and a prior at each pixel.
no code implementations • 5 Nov 2015 • Manjunath Narayana, Allen Hanson, Erik Learned-Miller
In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussians at each pixel [7], to kernel density estimates at each pixel [1], and more recently to joint domainrange density estimates that incorporate spatial information [6].
no code implementations • 5 Nov 2015 • Manjunath Narayana, Allen Hanson, Erik Learned-Miller
Our goal is to develop a segmentation algorithm that clusters pixels that have similar real-world motion irrespective of their depth in the scene.