Video Generation with Semantic Information
Masterarbeit
Im Rahmen des Projekts Semantic Scene Analysis

Description

With the development of neural networks, high-quality images can be generated automatically by different algorithms with semantic information. Go further, it is also possible to generate a video with few sentences or other semantic information.

In this project, when designing the generative model (e.g. Generative Adversarial Network), it is not only necessary to consider the location/shape/texture of the objects in each frame, but also to utilize the temporal dependences and constraints.

It is a challenging but potential work. Please send me email if you have interest and questions.

Key words: Generative adversarial network (GAN), video generation/video synthesis, semantic analysis, temporal dependencies, recurrent network.

Requirements

  • Python
  • Pytorch/Tensorflow
  • Neural Network/Deep Learning
  • Thirst for knowledge


Contact person: Yuren Cong