We have two midterm master project presentations on Friday, 18 September starting 15:45. The session will be on Zoom.

Presenter: Berend Baas

Title: Latent shape editing

Abstract: In recent years, deep learning on shapes and manifolds has been used to try and perform a variety of tasks, such as classification, deformation transfer and shape matching. This is often done through architectures such as Autoencoders or Generative Adversarial Networks, that try to learn a vector representation of training shapes, which is then used for downstream tasks.

However, current trained representations are generally poorly structured: Their latent space consists of manifolds that are entangled and highly non-linear. This makes it difficult to predict the results of modifications in the latent space on the output of the network. In this work, we investigate the latent space of shape networks, to try and develop techniques to obtain semantic deformations from latent editing operations. We consider two approaches: developing techniques to navigate complex entangles latent spaces, and developing less entangled and more interpretable representations, that can help in providing semantic editing operations.

Presenter: Ruben Vroegindeweij

Title: Depicting motion in a still image by spatio-temporal image fusion

Abstract: TBD

*Zoom meeting details upon request.