Dr Amir Atapour-Abarghouei amir.atapour-abarghouei@durham.ac.uk
Assistant Professor
Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach
Atapour-Abarghouei, A.; Breckon, T.P.
Authors
Professor Toby Breckon toby.breckon@durham.ac.uk
Professor
Citation
Atapour-Abarghouei, A., & Breckon, T. (2019). Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach. In IEEE Conference on Computer Vision and Pattern Recognition, Deep Vision Long Beach, CA, USA, 16-20 June 2019
Conference Name | IEEE/CVF Conference on Computer Vision and Pattern Recognition |
---|---|
Conference Location | Long Beach, California, USA |
Start Date | Jun 16, 2019 |
End Date | Jun 20, 2019 |
Acceptance Date | Feb 25, 2019 |
Publication Date | Jun 1, 2019 |
Deposit Date | Mar 25, 2019 |
Publicly Available Date | Nov 13, 2019 |
Publisher | Institute of Electrical and Electronics Engineers |
Book Title | IEEE Conference on Computer Vision and Pattern Recognition, Deep Vision Long Beach, CA, USA, 16-20 June 2019 |
Keywords | Monocular depth, Generative adversarial network, GAN, Depth map, Disparity, Depth from single image, Multiple task learning, Semantic segmantation, Temporal consistency |
Public URL | https://durham-repository.worktribe.com/output/1142446 |
Publisher URL | http://cvpr2019.thecvf.com/ |
Files
Accepted Conference Proceeding
(3 Mb)
PDF
You might also like
Region-based Appearance and Flow Characteristics for Anomaly Detection in Infrared Surveillance Imagery
(2023)
Conference Proceeding
A Feasibility Study on Image Inpainting for Non-cleft Lip Generation from Patients with Cleft Lip
(2022)
Conference Proceeding
“Just Drive”: Colour Bias Mitigation for Semantic Segmentation in the Context of Urban Driving
(2021)
Conference Proceeding
Transforming Fake News: Robust Generalisable News Classification Using Transformers
(2021)
Conference Proceeding
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search