Nikita Araslanov

I'm a postdoc in the Computer Vision Group at TU Munich and a visiting faculty at Google. I'm interested in semantic and 3D-based visual inference from video data. Previously, I completed a PhD in the Visual Inference Lab at 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).

26/02/2025 Two papers accepted at CVPR 2025! Code and preprints will be available soon.
15/12/2024 I joined Google as a visiting faculty researcher.
11/09/2024 Oral presentation at GCPR: CARLA Drone, a synthetic dataset for drone-view 2D/3D object detection and more.
03/07/2024 Introducing DiffCD: an SDF-based shape reconstruction approach from point clouds. To be presented at ECCV '24!

Practical Course

(SS25) Deep Learning for Spatial AI

Course page

Lecture

(WS24/25) Computer Vision 3: Segmentation, Detection and Tracking

Course details

	New!It’s a (Blind) Match! Towards Vision-Language Correspondence without Parallel Data Dominik Schnaus, Nikita Araslanov and Daniel Cremers Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (to appear) Paper (arXiv) \| Project webpage
	New!Scene-Centric Unsupervised Panoptic Segmentation Oliver Hahn^, Christoph Reich^, Nikita Araslanov, Daniel Cremers, Christian Rupprecht and Stefan Roth Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (to appear) Paper and code (coming soon)
	CARLA Drone: Monocular 3D Object Detection from a Different Perspective Johannes Meier, Luca Scalerandi, Oussema Dhaouadi, Jacques Kaiser, Nikita Araslanov and Daniel Cremers DAGM German Conference on Pattern Recognition (GCPR), 2024 (oral) Paper (arXiv) \| Project webpage
	DiffCD: A Symmetric Differentiable Chamfer Distance for Neural Implicit Surface Fitting Linus Härenstam-Nielsen, Lu Sang, Abhishek Saroha, Nikita Araslanov and Daniel Cremers European Conference on Computer Vision (ECCV), 2024 Paper (arXiv) \| Code
	Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals Oliver Hahn, Nikita Araslanov, Simone Schaub-Meyer and Stefan Roth Transactions on Machine Learning Research (TMLR), 2024 Paper \| Code
	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 Paper (arXiv) \| Code
	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) Paper \| Code
	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 Paper (arXiv) \| 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

	New!It’s a (Blind) Match! Towards Vision-Language Correspondence without Parallel Data Dominik Schnaus, Nikita Araslanov and Daniel Cremers Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (to appear) Paper (arXiv) \| Project webpage
	New!Scene-Centric Unsupervised Panoptic Segmentation Oliver Hahn^, Christoph Reich^, Nikita Araslanov, Daniel Cremers, Christian Rupprecht and Stefan Roth Conference on Computer Vision and Pattern Recognition (CVPR), 2025 (to appear) Paper and code (coming soon)
	CARLA Drone: Monocular 3D Object Detection from a Different Perspective Johannes Meier, Luca Scalerandi, Oussema Dhaouadi, Jacques Kaiser, Nikita Araslanov and Daniel Cremers DAGM German Conference on Pattern Recognition (GCPR), 2024 (oral) Paper (arXiv) \| Project webpage
	DiffCD: A Symmetric Differentiable Chamfer Distance for Neural Implicit Surface Fitting Linus Härenstam-Nielsen, Lu Sang, Abhishek Saroha, Nikita Araslanov and Daniel Cremers European Conference on Computer Vision (ECCV), 2024 Paper (arXiv) \| Code
	Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals Oliver Hahn, Nikita Araslanov, Simone Schaub-Meyer and Stefan Roth Transactions on Machine Learning Research (TMLR), 2024 Paper \| Code
	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 Paper (arXiv) \| Code
	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) Paper \| Code
	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 Paper (arXiv) \| 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

About

News

Teaching

Publications (Google Scholar )

New!It’s a (Blind) Match! Towards Vision-Language Correspondence without Parallel Data

New!Scene-Centric Unsupervised Panoptic Segmentation

CARLA Drone: Monocular 3D Object Detection from a Different Perspective

DiffCD: A Symmetric Differentiable Chamfer Distance for Neural Implicit Surface Fitting

Boosting Unsupervised Semantic Segmentation
with Principal Mask Proposals

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

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

Masked Event Modeling: Self-Supervised Pretraining for Event Cameras

Semantic Self-adaptation:
Enhancing Generalization with a Single Sample

Dense Unsupervised Learning for Video Segmentation

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation

Single-Stage Semantic Segmentation from Image Labels