1 code implementation • NeurIPS 2016 • Miguel A. Bautista, Artsiom Sanakoyeu, Ekaterina Sutter, Björn Ommer
Exemplar learning is a powerful paradigm for discovering visual similarities in an unsupervised manner.
2 code implementations • CVPR 2017 • Miguel A. Bautista, Artsiom Sanakoyeu, Björn Ommer
Similarity learning is then formulated as a partial ordering task with soft correspondences of all samples to classes.
no code implementations • 22 Feb 2018 • Artsiom Sanakoyeu, Miguel A. Bautista, Björn Ommer
Exemplar learning of visual similarities in an unsupervised manner is a problem of paramount importance to Computer Vision.
9 code implementations • ECCV 2018 • Artsiom Sanakoyeu, Dmytro Kotovenko, Sabine Lang, Björn Ommer
These and our qualitative results ranging from small image patches to megapixel stylistic images and videos show that our approach better captures the subtle nature in which a style affects content.
4 code implementations • 9 Apr 2019 • Yauhen Babakhin, Artsiom Sanakoyeu, Hirotoshi Kitamura
Seismic image analysis plays a crucial role in a wide range of industrial applications and has been receiving significant attention.
1 code implementation • CVPR 2019 • Artsiom Sanakoyeu, Vadim Tschernezki, Uta Büchler, Björn Ommer
Approaches for learning a single distance metric often struggle to encode all different types of relationships and do not generalize well.
1 code implementation • CVPR 2020 • Artsiom Sanakoyeu, Vasil Khalidov, Maureen S. McCarthy, Andrea Vedaldi, Natalia Neverova
Recent contributions have demonstrated that it is possible to recognize the pose of humans densely and accurately given a large dataset of poses annotated in detail.
1 code implementation • CVPR 2019 • Dmytro Kotovenko, Artsiom Sanakoyeu, Pingchuan Ma, Sabine Lang, Björn Ommer
Recent work has significantly improved the representation of color and texture and computational speed and image resolution.
no code implementations • 10 Sep 2020 • Akhmedkhan Shabanov, Ilya Krotov, Nikolay Chinaev, Vsevolod Poletaev, Sergei Kozlukov, Igor Pasechnik, Bulat Yakupov, Artsiom Sanakoyeu, Vadim Lebedev, Dmitry Ulyanov
Consumer-level depth cameras and depth sensors embedded in mobile devices enable numerous applications, such as AR games and face identification.
no code implementations • CVPR 2021 • Natalia Neverova, Artsiom Sanakoyeu, Patrick Labatut, David Novotny, Andrea Vedaldi
Recent work has shown that it is possible to learn a unified dense pose predictor for several categories of related objects.
1 code implementation • 9 Sep 2021 • Artsiom Sanakoyeu, Pingchuan Ma, Vadim Tschernezki, Björn Ommer
We propose to build a more expressive representation by jointly splitting the embedding space and the data hierarchically into smaller sub-parts.
3 code implementations • 5 Jun 2022 • Stepan Konev, Kirill Brodt, Artsiom Sanakoyeu
To plan a safe and efficient route, an autonomous vehicle should anticipate future motions of other agents around it.
1 code implementation • ICCV 2023 • Sara Rojas, Jesus Zarzar, Juan Camilo Perez, Artsiom Sanakoyeu, Ali Thabet, Albert Pumarola, Bernard Ghanem
Re-ReND is designed to achieve real-time performance by converting the NeRF into a representation that can be efficiently processed by standard graphics pipelines.
no code implementations • 25 Mar 2023 • Albert Pumarola, Artsiom Sanakoyeu, Lior Yariv, Ali Thabet, Yaron Lipman
Surface reconstruction has been seeing a lot of progress lately by utilizing Implicit Neural Representations (INRs).
1 code implementation • CVPR 2023 • Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
A particular challenge is that only a sparse tracking signal is available from standalone HMDs (Head Mounted Devices), often limited to tracking the user's head and wrists.
no code implementations • 21 Apr 2023 • Angela Castillo, Maria Escobar, Guillaume Jeanneret, Albert Pumarola, Pablo Arbeláez, Ali Thabet, Artsiom Sanakoyeu
To the best of our knowledge, this is the first approach that uses the reverse diffusion process to model full-body tracking as a conditional sequence generation task.
no code implementations • 6 Dec 2023 • Felix Wimbauer, Bichen Wu, Edgar Schoenfeld, Xiaoliang Dai, Ji Hou, Zijian He, Artsiom Sanakoyeu, Peizhao Zhang, Sam Tsai, Jonas Kohler, Christian Rupprecht, Daniel Cremers, Peter Vajda, Jialiang Wang
However, one of the major drawbacks of diffusion models is that the image generation process is costly.
no code implementations • 5 Feb 2024 • Andrey Davydov, Alexey Sidnev, Artsiom Sanakoyeu, Yuhua Chen, Mathieu Salzmann, Pascal Fua
When enough annotated training data is available, supervised deep-learning algorithms excel at estimating human body pose and shape using a single camera.