activity
20152017
most citedSceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor Trajectories with Ground Truth

91 citations · 160 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV201713 cited

Self-Supervised Siamese Learning on Stereo Image Pairs for Depth Estimation in Robotic Surgery

Menglong Ye, Edward Johns, Ankur Handa +3

Robotic surgery has become a powerful tool for performing minimally invasive procedures, providing advantages in dexterity, precision, and 3D vision, over traditional surgery. One…

cs.CV201791 cited

SceneNet RGB-D: 5M Photorealistic Images of Synthetic Indoor Trajectories with Ground Truth

John McCormac, Ankur Handa, Stefan Leutenegger +1

We introduce SceneNet RGB-D, expanding the previous work of SceneNet to enable large scale photorealistic rendering of indoor scene trajectories. It provides pixel-perfect ground t…

cs.CV2016

HDRFusion: HDR SLAM using a low-cost auto-exposure RGB-D sensor

Shuda Li, Ankur Handa, Yang Zhang +1

We describe a new method for comparing frame appearance in a frame-to-model 3-D mapping and tracking system using an low dynamic range (LDR) RGB-D camera which is robust to brightn…

cs.CV201556 cited

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling

Vijay Badrinarayanan, Ankur Handa, Roberto Cipolla

We propose a novel deep architecture, SegNet, for semantic pixel wise image labelling. SegNet has several attractive properties; (i) it only requires forward evaluation of a fully…

cs.CV2015

SynthCam3D: Semantic Understanding With Synthetic Indoor Scenes

Ankur Handa, Viorica Patraucean, Vijay Badrinarayanan +2

We are interested in automatic scene understanding from geometric cues. To this end, we aim to bring semantic segmentation in the loop of real-time reconstruction. Our semantic seg…