Bibliographic description:
Lazorenko, Anastasiya. Synthesizing novel views for Street View experience: Bachelor Thesis: manuscript / Anastasiya Lazorenko; Supervisor: Philipp Kofman; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2021. – 30 p.: ill.
Abstract:
Navigational applications often suffer from restricted and granular movement possibilities
caused by a limited capture of real-world locations. Even the largest collections
of street photos like Street-View, Mapillary [31], and SPED win more in geographical
coverage than in qualitative capture of specific scenes. A possible solution
to this problem could be post-processing of available image collections and generation
of new photos that would restore the missing parts. This is the task of novel
view synthesis - a known area in computer graphics and vision, that has shown impressive
results over last several years [26], [27], [33], etc. However, the problem of
real-world outdoor scene reconstruction is the most challenging, and is still a subject
to active research. In this work we will explore different approaches to novel
view synthesis and evaluate some of them on the sparse real-world imagery from
Street-View dataset.
