no code implementations • 16 Jan 2024 • Gen Li, Kaifeng Zhao, Siwei Zhang, Xiaozhong Lyu, Mihai Dusmanu, Yan Zhang, Marc Pollefeys, Siyu Tang
To address this challenge, we introduce EgoGen, a new synthetic data generator that can produce accurate and rich ground-truth training data for egocentric perception tasks.
no code implementations • 19 Oct 2022 • Paul-Edouard Sarlin, Mihai Dusmanu, Johannes L. Schönberger, Pablo Speciale, Lukas Gruber, Viktor Larsson, Ondrej Miksik, Marc Pollefeys
To close this gap, we introduce LaMAR, a new benchmark with a comprehensive capture and GT pipeline that co-registers realistic trajectories and sensor streams captured by heterogeneous AR devices in large, unconstrained scenes.
1 code implementation • 27 Sep 2022 • Hao Dong, Xieyuanli Chen, Mihai Dusmanu, Viktor Larsson, Marc Pollefeys, Cyrill Stachniss
A distinctive representation of image patches in form of features is a key component of many computer vision and robotics tasks, such as image matching, image retrieval, and visual localization.
1 code implementation • CVPR 2021 • Arda Düzçeker, Silvano Galliani, Christoph Vogel, Pablo Speciale, Mihai Dusmanu, Marc Pollefeys
We propose an online multi-view depth prediction approach on posed video streams, where the scene geometry information computed in the previous time steps is propagated to the current time step in an efficient and geometrically plausible way.
1 code implementation • ICCV 2021 • Mihai Dusmanu, Ondrej Miksik, Johannes L. Schönberger, Marc Pollefeys
Visual localization and mapping is the key technology underlying the majority of mixed reality and robotics systems.
no code implementations • CVPR 2021 • Mihai Dusmanu, Johannes L. Schönberger, Sudipta N. Sinha, Marc Pollefeys
Many computer vision systems require users to upload image features to the cloud for processing and storage.
1 code implementation • ECCV 2020 • Mihai Dusmanu, Johannes L. Schönberger, Marc Pollefeys
In this work, we address the problem of refining the geometry of local image features from multiple views without known scene or camera geometry.
1 code implementation • CVPR 2019 • Mihai Dusmanu, Ignacio Rocco, Tomas Pajdla, Marc Pollefeys, Josef Sivic, Akihiko Torii, Torsten Sattler
In this work we address the problem of finding reliable pixel-level correspondences under difficult imaging conditions.
4 code implementations • 9 May 2019 • Mihai Dusmanu, Ignacio Rocco, Tomas Pajdla, Marc Pollefeys, Josef Sivic, Akihiko Torii, Torsten Sattler
In this work we address the problem of finding reliable pixel-level correspondences under difficult imaging conditions.
Ranked #8 on Image Matching on IMC PhotoTourism
no code implementations • EMNLP 2017 • Mihai Dusmanu, Elena Cabrio, Serena Villata
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