1 code implementation • CVPR 2024 • Anna Kukleva, Fadime Sener, Edoardo Remelli, Bugra Tekin, Eric Sauser, Bernt Schiele, Shugao Ma
Lately, there has been growing interest in adapting vision-language models (VLMs) to image and third-person video classification due to their success in zero-shot recognition.
no code implementations • 26 Mar 2024 • Sammy Christen, Shreyas Hampali, Fadime Sener, Edoardo Remelli, Tomas Hodan, Eric Sauser, Shugao Ma, Bugra Tekin
In the grasping stage, the model only generates hand motions, whereas in the interaction phase both hand and object poses are synthesized.
no code implementations • 30 Nov 2023 • Evin Pınar Örnek, Yann Labbé, Bugra Tekin, Lingni Ma, Cem Keskin, Christian Forster, Tomas Hodan
Pose hypotheses are then generated from 2D-3D correspondences established by matching DINOv2 patch features between the query image and a retrieved template, and finally optimized by featuremetric refinement.
no code implementations • ICCV 2023 • Xin Wang, Taein Kwon, Mahdi Rad, Bowen Pan, Ishani Chakraborty, Sean Andrist, Dan Bohus, Ashley Feniello, Bugra Tekin, Felipe Vieira Frujeri, Neel Joshi, Marc Pollefeys
Building an interactive AI assistant that can perceive, reason, and collaborate with humans in the real world has been a long-standing pursuit in the AI community.
1 code implementation • CVPR 2022 • Taein Kwon, Bugra Tekin, Siyu Tang, Marc Pollefeys
Temporal alignment of fine-grained human actions in videos is important for numerous applications in computer vision, robotics, and mixed reality.
no code implementations • CVPR 2022 • Weizhe Liu, Bugra Tekin, Huseyin Coskun, Vibhav Vineet, Pascal Fua, Marc Pollefeys
To this end, we propose an approach to enforce temporal priors on the optimal transport matrix, which leverages temporal consistency, while allowing for variations in the order of actions.
no code implementations • 9 Sep 2021 • Dimitri Zhukov, Ignacio Rocco, Ivan Laptev, Josef Sivic, Johannes L. Schönberger, Bugra Tekin, Marc Pollefeys
Contrary to the standard scenario of instance-level 3D reconstruction, where identical objects or scenes are present in all views, objects in different instructional videos may have large appearance variations given varying conditions and versions of the same product.
no code implementations • ICCV 2021 • Taein Kwon, Bugra Tekin, Jan Stuhmer, Federica Bogo, Marc Pollefeys
To this end, we propose a method to create a unified dataset for egocentric 3D interaction recognition.
1 code implementation • 25 Aug 2020 • Dorin Ungureanu, Federica Bogo, Silvano Galliani, Pooja Sama, Xin Duan, Casey Meekhof, Jan Stühmer, Thomas J. Cashman, Bugra Tekin, Johannes L. Schönberger, Pawel Olszta, Marc Pollefeys
Mixed reality headsets, such as the Microsoft HoloLens 2, are powerful sensing devices with integrated compute capabilities, which makes it an ideal platform for computer vision research.
no code implementations • CVPR 2020 • Yana Hasson, Bugra Tekin, Federica Bogo, Ivan Laptev, Marc Pollefeys, Cordelia Schmid
Modeling hand-object manipulations is essential for understanding how humans interact with their environment.
Ranked #9 on hand-object pose on HO-3D
no code implementations • 22 Jul 2019 • Huseyin Coskun, Zeeshan Zia, Bugra Tekin, Federica Bogo, Nassir Navab, Federico Tombari, Harpreet Sawhney
The lack of large-scale real datasets with annotations makes transfer learning a necessity for video activity understanding.
1 code implementation • CVPR 2019 • Bugra Tekin, Federica Bogo, Marc Pollefeys
Given a single RGB image, our model jointly estimates the 3D hand and object poses, models their interactions, and recognizes the object and action classes with a single feed-forward pass through a neural network.
5 code implementations • CVPR 2018 • Bugra Tekin, Sudipta N. Sinha, Pascal Fua
For single object and multiple object pose estimation on the LINEMOD and OCCLUSION datasets, our approach substantially outperforms other recent CNN-based approaches when they are all used without post-processing.
Ranked #1 on 6D Pose Estimation using RGB on OCCLUSION
1 code implementation • ICCV 2017 • Bugra Tekin, Pablo Márquez-Neila, Mathieu Salzmann, Pascal Fua
Most recent approaches to monocular 3D human pose estimation rely on Deep Learning.
Ranked #289 on 3D Human Pose Estimation on Human3.6M
no code implementations • 17 May 2016 • Bugra Tekin, Isinsu Katircioglu, Mathieu Salzmann, Vincent Lepetit, Pascal Fua
Most recent approaches to monocular 3D pose estimation rely on Deep Learning.
Ranked #325 on 3D Human Pose Estimation on Human3.6M
no code implementations • CVPR 2016 • Bugra Tekin, Artem Rozantsev, Vincent Lepetit, Pascal Fua
We propose an efficient approach to exploiting motion information from consecutive frames of a video sequence to recover the 3D pose of people.
no code implementations • arXiv:1504.08200 Search... Help | Advanced Search 2015 • Bugra Tekin, Xiaolu Sun, Xinchao Wang, Vincent Lepetit, Pascal Fua
We propose an efficient approach to exploiting motion information from consecutive frames of a video sequence to recover the 3D pose of people.
Ranked #326 on 3D Human Pose Estimation on Human3.6M
no code implementations • 30 Apr 2015 • Bugra Tekin, Xiaolu Sun, Xinchao Wang, Vincent Lepetit, Pascal Fua
We propose an efficient approach to exploiting motion information from consecutive frames of a video sequence to recover the 3D pose of people.