546 citations · 861 across the 7 of their papers we have counts for
8 papers
EPOCH: Jointly Estimating the 3D Pose of Cameras and Humans
Nicola Garau, Giulia Martinelli, Niccolò Bisagno +2
Monocular Human Pose Estimation (HPE) aims at determining the 3D positions of human joints from a single 2D image captured by a camera. However, a single 2D point in the image may…
HumMUSS: Human Motion Understanding using State Space Models
Arnab Kumar Mondal, Stefano Alletto, Denis Tome
Understanding human motion from video is essential for a range of applications, including pose estimation, mesh recovery and action recognition. While state-of-the-art methods pred…
SelfPose: 3D Egocentric Pose Estimation from a Headset Mounted Camera
Denis Tome, Thiemo Alldieck, Patrick Peluse +4
We present a solution to egocentric 3D body pose estimation from monocular images captured from downward looking fish-eye cameras installed on the rim of a head mounted VR device.…
xR-EgoPose: Egocentric 3D Human Pose from an HMD Camera
Denis Tome, Patrick Peluse, Lourdes Agapito +1
We present a new solution to egocentric 3D body pose estimation from monocular images captured from a downward looking fish-eye camera installed on the rim of a head mounted virtua…
Rethinking Pose in 3D: Multi-stage Refinement and Recovery for Markerless Motion Capture
Denis Tome, Matteo Toso, Lourdes Agapito +1
We propose a CNN-based approach for multi-camera markerless motion capture of the human body. Unlike existing methods that first perform pose estimation on individual cameras and g…
Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image
Denis Tome, Chris Russell, Lourdes Agapito
We propose a unified formulation for the problem of 3D human pose estimation from a single raw RGB image that reasons jointly about 2D joint estimation and 3D pose reconstruction t…
Reduced Memory Region Based Deep Convolutional Neural Network Detection
Denis Tome', Luca Bondi, Emanuele Plebani +3
Accurate pedestrian detection has a primary role in automotive safety: for example, by issuing warnings to the driver or acting actively on car's brakes, it helps decreasing the pr…
Deep convolutional neural networks for pedestrian detection
Denis Tomè, Federico Monti, Luca Baroffio +3
Pedestrian detection is a popular research topic due to its paramount importance for a number of applications, especially in the fields of automotive, surveillance and robotics. De…