I'm a postdoc in the Computer Vision Group at TU Munich in Germany. My research focuses on visual scene understanding with limited supervision. Previously, I was a PhD student working at the Visual Inference Lab in TU Darmstadt. I obtained my Master's in Computer Science from University of Bonn. I also hold a Diploma degree in Mechanical Engineering from Moscow Aviation Institute (specialising in jets).


  • 16/01/2024 Our work on direct image alignment has been accepted at ICLR '24 (oral presentation, top 1.2%).
  • 20/10/2023 We will present a self-supervised approach for event data at WACV '24.
  • 19/07/2023 Our work on self-adaptive semantic segmentation has been published at TMLR.
  • 14/09/2022 I defended my PhD thesis "Deep Visual Parsing with Limited Supervision" with distinction (summa cum laude).



Computer Vision 3: Segmentation, Detection and Tracking

Course details (WS23/24)

Practical Course

Geometric Scene Understanding

Course page (SS24, TBA)


Flattening the Parent Bias:
Hierarchical Semantic Segmentation in the Poincaré Ball

Simon Weber, Barış Zöngür, Nikita Araslanov and Daniel Cremers

Conference on Computer Vision and Pattern Recognition (CVPR), 2024

To appear.

An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment

Sergei Solonets*, Daniil Sinitsyn*, Lukas Von Stumberg, Nikita Araslanov and Daniel Cremers

International Conference on Learning Representations (ICLR), 2024 (oral)

To appear.

Masked Event Modeling: Self-Supervised Pretraining for Event Cameras

Simon Klenk*, David Bonello*, Lukas Koestler*, Nikita Araslanov and Daniel Cremers

Winter Conference on Applications of Computer Vision (WACV), 2024

Preprint | Code

Semantic Self-adaptation:
Enhancing Generalization with a Single Sample

Sherwin Bahmani, Oliver Hahn, Eduard Zamfir, Nikita Araslanov, Daniel Cremers and Stefan Roth

Transactions on Machine Learning Research (TMLR), 2023

Paper | Code

Dense Unsupervised Learning for Video Segmentation

Nikita Araslanov, Simone Schaub-Meyer and Stefan Roth

Advances in Neural Information Processing Systems (NeurIPS), 2021

Paper | Supplemental | Code

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation

Nikita Araslanov and Stefan Roth

Conference on Computer Vision and Pattern Recognition (CVPR), 2021

Paper | Supplemental | Code

Single-Stage Semantic Segmentation from Image Labels

Nikita Araslanov and Stefan Roth

Conference on Computer Vision and Pattern Recognition (CVPR), 2020

Paper | Supplemental | Code

Google Scholar