📣 Help Shape the Future of UKRI's Gateway to Research (GtR)

We're improving UKRI's Gateway to Research and are seeking your input! If you would be interested in being interviewed about the improvements we're making and to have your say about how we can make GtR more user-friendly, impactful, and effective for the Research and Innovation community, please email gateway@ukri.org.

A 3D database of everyday objects for vision research (2016)

First Author: Hibbard P

Attributed to: Learning to see in depth: neural models of binocular stereopsis funded by BBSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1167/16.12.289

Publication URI: http://dx.doi.org/10.1167/16.12.289

Type: Journal Article/Review

Parent Publication: Journal of Vision

Issue: 12