Publications by Alexander Mathis

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

Olaf Blanke, Alexander Mathis, Merkourios Simos

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

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

Devis Tuia, Valentin Alexandre Guy Gabeff, Alexander Mathis

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

Solaiman Shokur, Silvestro Micera, Friedhelm Christoph Hummel, Mahdi Hamidi Rad, Alexander Mathis

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

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

Olaf Blanke, Alexander Mathis, Merkourios Simos

Proprioception is essential for perception and action. Like any other sense, proprioception is also subject to illusions. In this study, we model classic proprioceptive illusions in which tendon vibrations lead to biases in estimating the state of the body ...

Wiley2025

EPFL-Smart-Kitchen-30 Annotations and Poses

Solaiman Shokur, Silvestro Micera, Friedhelm Christoph Hummel, Mahdi Hamidi Rad, Alexander Mathis

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

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

Alexander Mathis

American Physiological Society2025

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

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

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

Task-driven neural network models predict neural dynamics of proprioception

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

Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task -driven modeling approach to investigate the neural code of p ...

Cell Press2024

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

Mathieu Salzmann, Alexander Mathis

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

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

Mathieu Salzmann, Alexander Mathis

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

Acquiring musculoskeletal skills with curriculum-based reinforcement learning - model weights

Alberto Silvio Chiappa, Alexander Mathis

Here we provide the weights of the neural network policies used for the analysis presented in our article. The archives whose names start with a number (01 - 32) correspond to the 32 curriculum steps to train the Baoding Balls policy which ranked first at ...

Zenodo2024

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

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

Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Zenodo2024

Keypoint-MoSeq: parsing behavior by linking point tracking to pose dynamics

Mackenzie Mathis, Alexander Mathis, Shaokai Ye

Keypoint tracking algorithms can flexibly quantify animal movement from videos obtained in a wide variety of settings. However, it remains unclear how to parse continuous keypoint data into discrete actions. This challenge is particularly acute because key ...

2024

WildCLIP: Scene and Animal Attribute Retrieval from Camera Trap Data with Domain-Adapted Vision-Language Models

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

Wildlife observation with camera traps has great potential for ethology and ecology, as it gathers data non-invasively in an automated way. However, camera traps produce large amounts of uncurated data, which is time-consuming to annotate. Existing methods ...

2024

Decoding the brain: From neural representations to mechanistic models

Mackenzie Mathis, Alexander Mathis

A central principle in neuroscience is that neurons within the brain act in concert to produce perception, cognition, and adaptive behavior. Neurons are organized into specialized brain areas, dedicated to different functions to varying extents, and their ...

CELL PRESS2024

SuperAnimal pretrained pose estimation models for behavioral analysis

Tian Qiu, Maxime Michel André Vidal, Mackenzie Mathis, Alexander Mathis, Shaokai Ye, Jessy Lauer, Steffen Schneider

Quantification of behavior is critical in diverse applications from neuroscience, veterinary medicine to animal conservation. A common key step for behavioral analysis is first extracting relevant keypoints on animals, known as pose estimation. However, re ...

Nature Research2024

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

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

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

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields: Processed data and trained models

Mathieu Salzmann, Alexander Mathis

HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields, CVPR 2024 Haozhe Qi, Chen Zhao, Mathieu Salzmann, Alexander Mathis. Affiliation: EPFL Date: June, 2024 Link to the CVPR article: https://openaccess.thecvf.com/conte ...

Zenodo2024

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

Mathieu Salzmann, Alexander Mathis

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

WildCLIP: Scene and animal attribute retrieval from camera trap data with domain-adapted vision-language models

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

WildCLIP: Scene and animal attribute retrieval from camera trap data with domain-adapted vision-language models ############# Authors: Valentin Gabeff, Marc Russwurm, Devis Tuia & Alexander Mathis Affiliation: EPFL Date: January, 2024 Link to the article: ...

Zenodo2024