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Alexander Mathis

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Related publications (38)

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MammAlps: A multi-view video behavior monitoring dataset of wild mammals in the Swiss Alps

Devis Tuia, Alexander Mathis, Valentin Alexandre Guy Gabeff

MammAlps is a multimodal and multi-view dataset of wildlife behavior monitoring. Nine camera-traps were placed at three monitoring sites in the Swiss National Park, from which we curated over 14 hours of video with audio, 2D segmentation maps and 8.5 hours ...

Zenodo2025

EPFL-Smart-Kitchen-30 Collected data

Silvestro Micera, Friedhelm Christoph Hummel, Solaiman Shokur, Alexander Mathis, Mahdi Hamidi Rad, Haozhe Qi, Franklin Leong, Andy Bonnetto, Matea Tashkovska

Understanding behavior requires datasets that capture humans while carrying out complex tasks. The kitchen is an excellent environment for assessing human motor and cognitive function, as many complex actions are naturally exhibited in kitchens from choppi ...

Zenodo2025

Tumor-specific cytolytic CD4 T cells mediate immunity against human cancer

Hatice Altug, Alexander Mathis, George Coukos, David Gfeller, Pedro Romero, Alexandre Harari, Xiaokang Li, Yen-Cheng Liu

CD4 T cells have been implicated in cancer immunity for their helper functions. Moreover, their direct cytotoxic potential has been shown in some patients with cancer. Here, by mining single-cell RNA-seq datasets, we identified CD4 T cell clusters displayi ...

2021

Task-driven neural network models predict neural dynamics of proprioception: Synthetic muscle spindle datasets

Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi

Here we provide the synthetic spindle datasets of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the synthetic generated training dataset of simulated muscle spindles during arm passive movements gene ...

Zenodo2024

Measuring and modeling the motor system with machine learning

Alexander Mathis, Mackenzie Mathis, Alessandro Marin Vargas, Sébastien Benjamin Hausmann

The utility of machine learning in understanding the motor system is promising a revolution in how to collect, measure, and analyze data. The field of movement science already elegantly incorporates theory and engineering principles to guide experimental w ...

2021

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

EPFL Infoscience2024

Data for Deep-learning models of the ascending proprioceptive pathway are subject to illusions

Olaf Blanke, Alexander Mathis, Merkourios Simos, Adriana Perez Rotondo, Florian Axel Raphaël David

Here we provide the data to run the code provided in github.

Data required to train and test the models in data.zip ~37 GB when uncompressed. This includes: cleaned_smooth: pre-processed data from FLAG3D and PCR dataset, the elbow flexion datasets u ...

Zenodo2025

Data for Contrasting action and posture coding with hierarchical deep neural network models of proprioception

Alexander Mathis, Mackenzie Mathis, Matthias Bethge

############# Contrasting action and posture coding with hierarchical deep neural network models of proprioception, eLife 2023 ############# Authors: Kai J Sandbrink, Pranav Mamidanna, Claudio Michaelis, Matthias Bethge, Mackenzie W Mathis and Alexander ...

Zenodo2024

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields

Mathieu Salzmann, Alexander Mathis, Chen Zhao, Haozhe Qi

Human hands are highly articulated and versatile at handling objects. Jointly estimating the 3D poses of a hand and the object it manipulates from a monocular camera is challenging due to frequent occlusions. Thus, existing methods often rely on intermedia ...

IEEE2024

Multi-animal pose estimation, identification and tracking with DeepLabCut

Alexander Mathis, Mackenzie Mathis, Shaokai Ye, Steffen Schneider, Jessy Lauer, Mu Zhou

Estimating the pose of multiple animals is a challenging computer vision problem: frequent interactions cause occlusions and complicate the association of detected keypoints to the correct individuals, as well as having highly similar looking animals that ...

Nature Publishing Group2022

Synthetic data (Part 2) for "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields"

Mathieu Salzmann, Alexander Mathis, Chen Zhao, Haozhe Qi

Here we provide the data of our article "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields". It contains the rendered images and the segmentation masks that we use to train our model on HO3Dv2 dataset. The overall str ...

Zenodo2024

Neural and algorithmic bases of odor guided trail following in mice

Alexander Mathis

Oxford Univ Press2023

Tumor-Specific Cytolytic Cd4 T Cells Mediate Protective Immunity Against Human Cancer

Hatice Altug, Alexander Mathis, George Coukos, David Gfeller, Pedro Romero, Alexandre Harari, Xiaokang Li, Yen-Cheng Liu

BMJ PUBLISHING GROUP2020

Deep learning tools for the analysis of movement, identity and behavior

Alexander Mathis

OXFORD UNIV PRESS INC2021

Scene and animal attributes retrieval from camera trap data with domain-adapted language-vision models

Devis Tuia, Alexander Mathis, Marc Conrad Russwurm, Valentin Alexandre Guy Gabeff

2023

Rethinking pose estimation in crowds: overcoming the detection information bottleneck and ambiguity

Alexander Mathis, Mackenzie Mathis, Mu Zhou, Lucas Maximilian Stoffl

Here we provide neural networks weights for the best models in our article "Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity", ICCV 2023. Each model has the naming convention "dataset"-"modeltype".pth. Th ...

Zenodo2023

Synthetic data (Part 1) for "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields"

Mathieu Salzmann, Alexander Mathis, Chen Zhao, Haozhe Qi

Here we provide the data of our article "HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields". It contains the preprocessed SDF samples. Meanwhile, we also include rendered data for HO3Dv2 here. The overall structure of ...

Zenodo2024

Climbing out of the lab: studying motor planning and coarticulation in the climbing gym

Alexander Mathis, Andy Bonnetto

American Physiological Society2025