Multi-animal pose estimation, identification and tracking with DeepLabCut

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Human vision has evolved to make sense of a world in which elements almost never appear in isolation. Surprisingly, the recognition of an element in a visual scene is strongly limited by the presence of other nearby elements, a phenomenon known as visual c ...

Decoding visual cognition from non-invasive measurements of brain activity has shown valuable applications. Vision-based Brain-Computer Interfaces (BCI) systems extend from spellers to database search and spatial navigation. Despite the high performance of ...

Non-verbal behaviours play an important role in human communication since it can indicate human attention, serve as communication cue in interactions, or even reveal higher level personal constructs. For instance, head nod, a common non-verbal behaviour, c ...

With ever greater computational resources and more accessible software, deep neural networks have become ubiquitous across industry and academia. Their remarkable ability to generalize to new samples defies the conventional view, which holds that complex, ...

Most recent 6D pose estimation frameworks first rely on a deep network to establish correspondences between 3D object keypoints and 2D image locations and then use a variant of a RANSAC-based Perspective-n-Point (PnP) algorithm. This two-stage process, how ...

Due to their wide field of view, omnidirectional cameras are frequently used by autonomous vehicles, drones and robots for navigation and other computer vision tasks. The images captured by such cameras, are often analyzed and classified with techniques de ...

Mapping the large neural networks of animal and human brains is a fundamental but so far elusive task, because of the massive amount of data and the consequent prohibitively long image taking and processing times. We developed an effective strategy called ...

Self-organized collective behavior has been analyzed in diverse types of gregarious animals. Such collective intelligence emerges from the synergy between individuals, which behave at their own time and spatial scales and without global rules. Recently, ro ...

Achieving robust multi-person 2D body landmark localization and pose estimation is essential for human behavior and interaction understanding as encountered for instance in HRI settings. Accurate methods have been proposed recently, but they usually rely o ...

Our goal is to capture the pose of neuroscience model organisms, without using any manual supervision, to be able to study how neural circuits orchestrate behaviour. Human pose estimation attains remarkable accuracy when trained on real or simulated datase ...

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 ...

How an animal allocates time and energy to different activities has repercussions for its survival, fitness, and response to changing environmental conditions. Fine-scale information on animal behaviour and energy expenditure can help develop better inform ...

Multi-animal pose estimation, identification and tracking with DeepLabCut

Chattez avec Graph Search

Crowding and the importance of grouping and segmentation processes in human vision

Towards everyday brain-computer interfacing through decoding visual cognition

Accurate Nod and 3D Gaze Estimation for Social Interaction Analysis

Evaluating and Interpreting Deep Convolutional Neural Networks via Non-negative Matrix Factorization

Single-Stage 6D Object Pose Estimation

Geometry Aware Convolutional Filters for Omnidirectional Images Representation

A synchrotron X-ray imaging strategy to map large animal brains

Robots mediating interactions between animals for interspecies collective behaviors

Efficient Convolutional Neural Networks for Depth-Based Multi-Person Pose Estimation

Deformation-aware Unpaired Image Translation for Pose Estimation on Laboratory Animals

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

Sensor and the Beast: Generalised Methods to Recognise Animal Behaviour and Quantify Energy Expenditure Using Inertial Sensors, and Applications