Deep Learning-Based Approaches for Shot Transition Detection and Known-Item Search in Video

This repository contains LaTeX source codes of my master thesis Deep Learning-Based Approaches for Shot Transition Detection and Known-Item Search in Video oficially available in Charles University Digital repository (dspace.cuni.cz).

Part of the work is presented in the following papers but the thesis contains further evaluations, ablation studies and implementation details:

• Souček, T., & Lokoč, J. (2020). TransNet V2: An effective deep network architecture for fast shot transition detection. arXiv preprint arXiv:2008.04838.

• Lokoč, J., Souček, T., Veselý, P., Mejzlík, F., Ji, J., Xu, C., & Li, X. (2020, October). A W2VV++ case study with automated and interactive text-to-video retrieval. In Proceedings of the 28th ACM International Conference on Multimedia (pp. 2553-2561).

💾 Experimets

The source code for the first part of the thesis regarding shot transition detection model TransNetV2 is available here .

The source code for the sencond part of the thesis regarding text retrieval model W2VV++BERT is available here .

📕 LaTeX Compilation

The source code can be compiled into PDF file using pdfLaTex by running pdflatex thesis.tex; bibtex thesis.aux; pdflatex thesis.tex; pdflatex thesis.tex from src directory or importing it into Overleaf. The compiled PDF file is available in this repository as Thesis.pdf or in Charles University Digital repository.