I am a second-year PhD student supervised by Prof. Andreas Geiger and I am also part of the machine learning team of the ETAS GmbH, Bosch Group. My research focuses on 3D reconstruction and generative models for 3D objects. I am particularly interested in investigating novel object representation that are feasible for learning-based methods.
One of the most challenging tasks of Computer Vision is to endow computers with the ability to discover the underlying relationships between the objects in a scene. The large amount of available labeled data as well as the fast progress in deep learning has significantly advanced many Computer Vision tasks, such as object segmentation. optical flow estimation, action recognition etc. However, a truly intelligent system would ideally be able to infer high-level semantics underlying human actions such as motivation, intent and emotion. However, all human actions involve some uncertainty. To this end, I would like to either develop or to further enhance existing methodologies that incorporate such uncertainties. For now, I have worked on the 3D reconstruction task, by developing a model able to incorporate uncertainties in the image formation process..
My research interest lies in the intersection of Computer Vision, Computer Graphics and Machine Learning. Currently I am working on reflectance and material estimation from RGB video input.