Sithu Aung

I am a PhD student in the Visual Recognition Group at the Czech Technical University in Prague, supervised by Zuzana Kúkelová, and co-supervised by Torsten Sattler. Before this, I completed my M.S. and worked as an intern researcher in the Visual Intelligence Group at the Korea Institute of Science and Technology / University of Science and Technology, Korea, under Junghyun Cho.

Email  /  GitHub  /  Google Scholar

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Research

My research interests span 3D Vision, Scene Reconstruction & Understanding, and Digital Twins.

* denotes equal contribution.

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Depth2Pose: A Pose-Based Benchmark for Monocular Depth Estimation without Ground-Truth Depth


Viktor Kocur*, Sithu Aung*, Gabrielle Flood*, Yaqing Ding, Lukas Bujnak, Torsten Sattler, Zuzana Kukelova
arXiv, 2026
paper / code / website /

A task-driven evaluation framework for monodepth based on depth-aware relative pose estimation, and a new dataset connected to this.

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Pseudo-Labeling via Video Object Tracking for Scalable Monocular 3D Object Detection


Seokyeong Lee*, Sithu Aung*, Junyong Choi, Seungryong Kim, Ig-Jae Kim, Junghyun Cho
arXiv, 2025
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A training-free pseudo-labeling framework for 3D object detection.

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Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset


Sithu Aung, Min-Cheol Sagong, Junghyun Cho
The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025
paper / website /

A new occupancy prediction dataset for dense pedestrians in multi-view environments.

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Enhancing Multi-view Pedestrian Detection Through Generalized 3D Feature Pulling


Sithu Aung, Haesol Park, Hyungjoo Jung, Junghyun Cho
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024
paper / youtube /

An effective 3D feature pulling method for generalizable multi-view pedestrian detection.




Services

Reviewer: ICCV 2025, BMVC 2025, CVPR 2026, ECCV 2026, NeurIPS 2026.




Design and source code from Jon Barron's website