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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Scientific Work
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Posts
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Blog Post number 1
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publications
An adaptive pig face recognition approach using Convolutional Neural Networks
Published in Computers and Electronics in Agriculture, 2020
In this paper, a novel framework composed of computer vision algorithms, machine learning and deep learning techniques is proposed to offer a relatively low-cost and scalable solution of pig recognition.
Recommended citation: Marsot, Mathieu and Mei, Jiangqiang and Shan, Xiaocai and Ye, Liyong and Feng, Peng and Yan, Xuejun and Li, Chenfan and Zhao, Yifan "An adaptive pig face recognition approach using Convolutional Neural Networks." Computers and Electronics in Agriculture. 1(1). https://www.sciencedirect.com/science/article/pii/S0168169920300673
A Structured Latent Space for Human Body Motion Generation
Published in 2022 International Conference on 3D Vision (3DV), 2022
This paper proposes a framework to learn a structured latent space to represent 4D human body motion, where each latent vector encodes a full motion of the whole 3D human shape
Recommended citation: Marsot, Mathieu and Wuhrer, Stefanie and Franco, Jean-Sébastien and Durocher, Stephane. (2022). "A Structured Latent Space for Human Body Motion Generation." 2022 International Conference on 3D Vision (3DV). 1(1). https://hal.science/hal-03250297/file/A_structure_latent_space_for_human_body_motion_generation.pdf
Representing motion as a sequence of latent primitives, a flexible approach for human motion modelling
Published in HAL, 2022
This paper proposes a new representation of human body motion which encodes a full motion in a sequence of latent motion primitives.
Recommended citation: Marsot, Mathieu and Wuhrer, Stefanie and Franco, Jean-Sebastien and Olivier, Anne Hélène. (2022). "Representing motion as a sequence of latent primitives, a flexible approach for human motion modelling Number 2." HAL. 1(2). https://hal.science/hal-03715820v2
Correspondence-free online human motion retargeting
Published in HAL, 2023
This paper presents a novel data-driven framework for unsupervised human motion retargeting which animates a target body shape with a source motion. This allows to retarget motions between different characters by animating a target subject with a motion of a source subject.
Recommended citation: Marsot, Mathieu and Rekik, Rim and Wuhrer, Stefanie and Franco, Jean-Sébastien and Olivier, Anne-Hélène. (2023). "Correspondence-free online human motion retargeting." HAL. 1(3). https://hal.inria.fr/hal-03970689v1/file/Motion_retargeting_CVPR_2023.pdf