Abstract
Cross view image translation is a challenging case of viewpoint translation which involves generating the street view image when the aerial view image is given and vice versa. As there is no overlap in the two views, a single stage generation network fails to capture the complex scene structure of objects in these two views. Our work aims to tackle the task of generating street level view images from aerial view images on the benchmarking CVUSA dataset by a cascade pipeline consisting of three smaller stages: street view image generation, semantic segmentation map generation, and image refinement, trained together in a constrained manner in a Conditional GAN (CGAN) framework. Our contributions are twofold: (1) The first stage of our pipeline examines the use of alternate architectures ResNet, ResUnet++ in a framework similar to the current State-of-the-Art (SoA), leading to useful insights and comparable or improved results in some cases. (2) In the 3rd stage, ResUNet++ is used for the first time for image refinement. U-net performs the best for street view image generation and semantic map generation as a result of the skip connections between encoders and decoders, while ResU-Net++ performs the best for image refinement because of the presence of the attention module in the decoders. Qualitative and quantitative comparisons with existing methods show that our model outperforms all others on the KL Divergence metric and ranks amongst the best for other metrics.
Original language | English |
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Title of host publication | PROCEEDINGS OF THE 17TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISAPP), VOL 4 |
Editors | GM Farinella, P Radeva, K Bouatouch |
Publisher | SCITEPRESS |
Pages | 372-379 |
Number of pages | 8 |
ISBN (Print) | 9789897585555 |
DOIs | |
Publication status | Published - 2022 |
Event | 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) / 17th International Conference on Computer Vision Theory and Applications (VISAPP) - Online Streaming Duration: 6 Feb 2022 → 8 Feb 2022 http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=132548©ownerid=45217 |
Publication series
Series | VISIGRAPP. Proceedings |
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ISSN | 2184-4321 |
Conference
Conference | 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP) / 17th International Conference on Computer Vision Theory and Applications (VISAPP) |
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Period | 6/02/22 → 8/02/22 |
Internet address |
Keywords
- Cross View Image Translation
- Conditional GANs
- Semantic Segmentation
- U-net