In this paper, we present a mixed-reality dataset of hand-occluded containers for category-level 6D object pose and size estimation.
no code implementations • 27 Jul 2021 • Alessio Xompero, Santiago Donaher, Vladimir Iashin, Francesca Palermo, Gökhan Solak, Claudio Coppola, Reina Ishikawa, Yuichi Nagao, Ryo Hachiuma, Qi Liu, Fan Feng, Chuanlin Lan, Rosa H. M. Chan, Guilherme Christmann, Jyun-Ting Song, Gonuguntla Neeharika, Chinnakotla Krishna Teja Reddy, Dinesh Jain, Bakhtawar Ur Rehman, Andrea Cavallaro
In this paper, we present a range of methods and an open framework to benchmark acoustic and visual perception for the estimation of the capacity of a container, and the type, mass, and amount of its content.
We investigate the problem of classifying - from a single image - the level of content in a cup or a drinking glass.
The 3D localisation of an object and the estimation of its properties, such as shape and dimensions, are challenging under varying degrees of transparency and lighting conditions.
In this paper, we propose an on-line variational Bayesian model for multi-person tracking from cluttered visual observations provided by person detectors.