activity
20152020
most citedToward Geometric Deep SLAM

45 citations · 55 across the 3 of their papers we have counts for

collaborators

14 papers

cs.CV2020

MagicEyes: A Large Scale Eye Gaze Estimation Dataset for Mixed Reality

Zhengyang Wu, Srivignesh Rajendran, Tarrence van As +3

With the emergence of Virtual and Mixed Reality (XR) devices, eye tracking has received significant attention in the computer vision community. Eye gaze estimation is a crucial com…

cs.CV2020

Scan2Plan: Efficient Floorplan Generation from 3D Scans of Indoor Scenes

Ameya Phalak, Vijay Badrinarayanan, Andrew Rabinovich

We introduce Scan2Plan, a novel approach for accurate estimation of a floorplan from a 3D scan of the structural elements of indoor environments. The proposed method incorporates a…

cs.CV2020

Atlas: End-to-End 3D Scene Reconstruction from Posed Images

Zak Murez, Tarrence van As, James Bartolozzi +3

We present an end-to-end 3D reconstruction method for a scene by directly regressing a truncated signed distance function (TSDF) from a set of posed RGB images. Traditional approac…

cs.CV2020

DELTAS: Depth Estimation by Learning Triangulation And densification of Sparse points

Ayan Sinha, Zak Murez, James Bartolozzi +2

Multi-view stereo (MVS) is the golden mean between the accuracy of active depth sensing and the practicality of monocular depth estimation. Cost volume based approaches employing 3…

cs.CV2019

SuperGlue: Learning Feature Matching with Graph Neural Networks

Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz +1

This paper introduces SuperGlue, a neural network that matches two sets of local features by jointly finding correspondences and rejecting non-matchable points. Assignments are est…

cs.CV2019

Efficient 2.5D Hand Pose Estimation via Auxiliary Multi-Task Training for Embedded Devices

Prajwal Chidananda, Ayan Sinha, Adithya Rao +2

2D Key-point estimation is an important precursor to 3D pose estimation problems for human body and hands. In this work, we discuss the data, architecture, and training procedure n…