Scholar
Nikita Araslanov
Google Scholar ID: RdMFioAAAAAJ
TU Munich | Google
Citations & Impact
Citations
974
H-index
10
i10-index
10
Publications
20
Co-authors
27
list available
Publications
Resume (English only)
Academic Achievements
- One paper accepted at NeurIPS 2025 as a spotlight.
- One workshop paper accepted at ICCV 2025 as a spotlight talk.
- BA-Track: dynamic scene reconstruction with bundle adjustment. Accepted at ICCV 2025 as an oral presentation and an award candidate!
- Two papers accepted at CVPR 2025.
- Serving as an Area Chair at CVPR 2025.
- Multiple publications in top conferences such as NeurIPS, ICCV, CVPR, etc.
- Involved in several research projects including FlowFeat, BA-Track, It’s a (Blind) Match!, Scene-Centric Unsupervised Panoptic Segmentation, CARLA Drone, DiffCD, 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, etc.
Research Experience
- Serves as a postdoctoral researcher at TU Munich and a visiting faculty researcher at Google. Teaches the Practical Course 'Deep Learning for Spatial AI' and the Lecture 'Computer Vision 3: Segmentation, Detection and Tracking'.
Education
- Earned his PhD in Computer Science from TU Darmstadt in the Visual Inference Lab, graduating with highest distinction; holds a Master's degree in Computer Science from the University of Bonn, where he graduated with distinction in 2016.
Background
- A postdoctoral researcher in the Computer Vision Group at TU Munich and a visiting faculty member at Google. His research focuses on semantic and 3D visual inference from video data, aiming to bridge perception and understanding in complex visual scenes.
Miscellany
- No relevant information provided
