  With the increasing number of online learning material in the web, search for
specific content in lecture videos can be time consuming. Therefore, automatic
slide extraction from the lecture videos can be helpful to give a brief
overview of the main content and to support the students in their studies. For
this task, we propose a deep learning method to detect slide transitions in
lectures videos. We first process each frame of the video by a heuristic-based
approach using a 2-D convolutional neural network to predict transition
candidates. Then, we increase the complexity by employing two 3-D convolutional
neural networks to refine the transition candidates. Evaluation results
demonstrate the effectiveness of our method in finding slide transitions.
