1 code implementation • ICCV 2023 • Manuel Kaufmann, Jie Song, Chen Guo, Kaiyue Shen, Tianjian Jiang, Chengcheng Tang, Juan Zarate, Otmar Hilliges
EMDB is a novel dataset that contains high-quality 3D SMPL pose and shape parameters with global body and camera trajectories for in-the-wild videos.
no code implementations • 9 Aug 2023 • Nina Weng, Martyna Plomecka, Manuel Kaufmann, Ard Kastrati, Roger Wattenhofer, Nicolas Langer
Eye movements can reveal valuable insights into various aspects of human mental processes, physical well-being, and actions.
no code implementations • CVPR 2023 • Yifei Yin, Chen Guo, Manuel Kaufmann, Juan Jose Zarate, Jie Song, Otmar Hilliges
We propose Hi4D, a method and dataset for the automatic analysis of physically close human-human interaction under prolonged contact.
1 code implementation • CVPR 2023 • Kaiyue Shen, Chen Guo, Manuel Kaufmann, Juan Jose Zarate, Julien Valentin, Jie Song, Otmar Hilliges
Our method models bodies, hands, facial expressions and appearance in a holistic fashion and can be learned from either full 3D scans or RGB-D data.
1 code implementation • CVPR 2023 • Zicong Fan, Omid Taheri, Dimitrios Tzionas, Muhammed Kocabas, Manuel Kaufmann, Michael J. Black, Otmar Hilliges
In part this is because there exist no datasets with ground-truth 3D annotations for the study of physically consistent and synchronised motion of hands and articulated objects.
1 code implementation • ICCV 2021 • Manuel Kaufmann, Yi Zhao, Chengcheng Tang, Lingling Tao, Christopher Twigg, Jie Song, Robert Wang, Otmar Hilliges
To this end, we present a method to estimate SMPL parameters from 6-12 EM sensors.
1 code implementation • 22 Oct 2020 • Manuel Kaufmann, Emre Aksan, Jie Song, Fabrizio Pece, Remo Ziegler, Otmar Hilliges
At the heart of our approach lies the idea to cast motion infilling as an inpainting problem and to train a convolutional de-noising autoencoder on image-like representations of motion sequences.
1 code implementation • 18 Apr 2020 • Emre Aksan, Manuel Kaufmann, Peng Cao, Otmar Hilliges
We propose a novel Transformer-based architecture for the task of generative modelling of 3D human motion.
1 code implementation • ICCV 2019 • Emre Aksan, Manuel Kaufmann, Otmar Hilliges
This is implemented via a hierarchy of small-sized neural networks connected analogously to the kinematic chains in the human body as well as a joint-wise decomposition in the loss function.
1 code implementation • 10 Oct 2018 • Yinghao Huang, Manuel Kaufmann, Emre Aksan, Michael J. Black, Otmar Hilliges, Gerard Pons-Moll
To learn from sufficient data, we synthesize IMU data from motion capture datasets.