1 code implementation • ICCV 2021 • Isinsu Katircioglu, Helge Rhodin, Jörg Spörri, Mathieu Salzmann, Pascal Fua
Self-supervised detection and segmentation of foreground objects aims for accuracy without annotated training data.
no code implementations • 11 Nov 2020 • Isinsu Katircioglu, Helge Rhodin, Victor Constantin, Jörg Spörri, Mathieu Salzmann, Pascal Fua
While supervised object detection and segmentation methods achieve impressive accuracy, they generalize poorly to images whose appearance significantly differs from the data they have been trained on.
no code implementations • 30 Aug 2019 • Roman Bachmann, Jörg Spörri, Pascal Fua, Helge Rhodin
We propose a method for estimating an athlete's global 3D position and articulated pose using multiple cameras.
no code implementations • 18 Jul 2019 • Isinsu Katircioglu, Helge Rhodin, Victor Constantin, Jörg Spörri, Mathieu Salzmann, Pascal Fua
While supervised object detection methods achieve impressive accuracy, they generalize poorly to images whose appearance significantly differs from the data they have been trained on.
no code implementations • CVPR 2018 • Helge Rhodin, Jörg Spörri, Isinsu Katircioglu, Victor Constantin, Frédéric Meyer, Erich Müller, Mathieu Salzmann, Pascal Fua
Accurate 3D human pose estimation from single images is possible with sophisticated deep-net architectures that have been trained on very large datasets.