Neural scene representations for learning-based view synthesis

Thesis event information

Date and time of the thesis defence

Place of the thesis defence

L10, Linnanmaa campus

Topic of the dissertation

Neural scene representations for learning-based view synthesis

Doctoral candidate

Phong Nguyen

Faculty and unit

University of Oulu Graduate School, Faculty of Information Technology and Electrical Engineering, Center for Machine Vision and Signal Analysis (CMVS)

Subject of study

3D Computer Vision, Deep Learning


Professor Serge Belongie, University of Copenhagen


Professor Janne Heikkilä, University of Oulu

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Generating new views from a collections of images

This thesis introduces learning-based novel view synthesis approaches using different neural scene representations. Traditional representations, such as voxels or point clouds, are often computationally expensive and challenging to work with. Neural scene representations, on the other hand, can be more compact and efficient, allowing faster processing and better performance. Additionally, neural scene representations can be learned end-to-end from data, enabling them to be adapted to specific tasks and domains.
Last updated: 23.1.2024