Marko Mihajlovic

PhD student
CAB G 89

Basic Information

I am a PhD student at ETH Zurich supervised by Prof. Dr. Siyu Tang since September 2020. Previously, I obtained my Master's degree at ETH as a part of the Direct Doctorate in Computer Science.

My research lies at the intersection of computer vision, machine learning, and computer graphics. I am particularly interested in realistic reconstruction of the 3D world around us and understanding how we, as humans, interact with the environment.


Authors:Marko MihajlovicSergey ProkudinMarc PollefeysSiyu Tang

ResField layers incorporates time-dependent weights into MLPs to effectively represent complex temporal signals.

Authors:Marko Mihajlovic , Shunsuke Saito , Aayush Bansal , Michael Zollhoefer  and Siyu Tang

COAP is a novel neural implicit representation for articulated human bodies that provides an efficient mechanism for modeling self-contacts and interactions with 3D environments.

Authors:Shaofei Wang, Marko Mihajlovic, Qianli Ma, Andreas Geiger, Siyu Tang

MetaAvatar is meta-learned model that represents generalizable and controllable neural signed distance fields (SDFs) for clothed humans. It can be fast fine-tuned to represent unseen subjects given as few as 8 monocular depth images.

Authors:Marko MihajlovicSilvan WederMarc PollefeysMartin R. Oswald

DeepSurfels is a novel 3D representation for geometry and appearance information that combines planar surface primitives with voxel grid representation for improved scalability and rendering quality.

Authors:Marko Mihajlovic, Yan Zhang, Michael J. Black and Siyu Tang

LEAP is a neural network architecture for representing volumetric animatable human bodies. It follows traditional human body modeling techniques and leverages a statistical human prior to generalize to unseen humans.