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Multi-animal pose estimation, identification and tracking with DeepLabCut

Publications associées (32)

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Learning Robust Features and Latent Representations for Single View 3D Pose Estimation of Humans and Objects

Bugra Tekin

Estimating the 3D poses of rigid and articulated bodies is one of the fundamental problems of Computer Vision. It has a broad range of applications including augmented reality, surveillance, animation and human-computer interaction. Despite the ever-growin ...

EPFL2018

Eigendecomposition-free Training of Deep Networks with Zero Eigenvalue-based Losses

Pascal Fua, Mathieu Salzmann, Zheng Dang, Kwang Moo Yi, Fei Wang, Yinlin Hu

Many classical Computer Vision problems, such as essential matrix computation and pose estimation from 3D to 2D correspondences, can be solved by ﬁnding the eigenvector corresponding to the smallest, or zero, eigenvalue of a matrix representing a linear sy ...

2018

Detailed classification of swimming paths in the Morris Water Maze: multiple strategies within one trial

Maria del Carmen Sandi Perez, Eleni Vasilaki, Gediminas Luksys

The Morris Water Maze is a widely used task in studies of spatial learning with rodents. Classical performance measures of animals in the Morris Water Maze include the escape latency, and the cumulative distance to the platform. Other methods focus on clas ...

Nature Publishing Group2015

Biologically Inspired Keypoints

Alexandre Massoud Alahi

This chapter describes methods to extract and represent biologically inspired keypoints. It highlights the design choices that are not contradictory to the current understanding of the human visual system (HVS). The chapter briefly defines some terminologi ...

Wiley2015

Mechanosensory interactions drive collective behaviour in Drosophila

Dario Floreano, Pavan P Ramdya, Pawel Lichocki, Lukas Frisch, Winnie Wing Yee Tse

Collective behaviour enhances environmental sensing and decision-making in groups of animals. Experimental and theoretical investigations of schooling fish, flocking birds and human crowds have demonstrated that simple interactions between individuals can ...

2015

Saliency-based Representations and Multi-component Classifiers for Visual Scene Recognition

Marco Fornoni

Visual scene recognition deals with the problem of automatically recognizing the high-level semantic concept describing a given image as a whole, such as the environment in which the scene is occurring (e.g. a mountain), or the event that is taking place ( ...

École Polytechnique Fédérale de Lausanne (EPFL)2014

Saliency-based representations and multi-component classifiers for visual scene recognition

Marco Fornoni

EPFL2014

Object Classification and Detection in High Dimensional Feature Space

Charles Dubout

Object classification and detection aim at recognizing and localizing objects in real-world images. They are fundamental computer vision problems and a prerequisite for full scene understanding. Their difficulty lies in the large number of possible object ...

Programme doctoral en Informatique, Communications et Information2013

Various computer visions tasks require a summary of visually important regions in an image. Thus, developing simple yet accurate salient region detection algorithms has become an important research topic. The currently best performing state-of-the-art sali ...

2013

Accessing 3R information for fundamental research is difficult for many reasons: the titles, abstracts, and author keywords of scientific articles do not contain the terms 3R, Reduce, Refine, Replace, alternatives or replacement. Mesh terms in Pubmed or th ...

2013