Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Lauri, Mikko"'
We investigate cross-quality knowledge distillation (CQKD), a knowledge distillation method where knowledge from a teacher network trained with full-resolution images is transferred to a student network that takes as input low-resolution images. As i
Externí odkaz:
http://arxiv.org/abs/2304.07593
Noisy sensing, imperfect control, and environment changes are defining characteristics of many real-world robot tasks. The partially observable Markov decision process (POMDP) provides a principled mathematical framework for modeling and solving robo
Externí odkaz:
http://arxiv.org/abs/2209.10342
It is often desired to train 6D pose estimation systems on synthetic data because manual annotation is expensive. However, due to the large domain gap between the synthetic and real images, synthesizing color images is expensive. In contrast, this do
Externí odkaz:
http://arxiv.org/abs/2103.01977
Autor:
Lauri, Mikko, Oliehoek, Frans A.
Multi-agent active perception is a task where a team of agents cooperatively gathers observations to compute a joint estimate of a hidden variable. The task is decentralized and the joint estimate can only be computed after the task ends by fusing ob
Externí odkaz:
http://arxiv.org/abs/2010.11835
3D scene models are useful in robotics for tasks such as path planning, object manipulation, and structural inspection. We consider the problem of creating a 3D model using depth images captured by a team of multiple robots. Each robot selects a view
Externí odkaz:
http://arxiv.org/abs/2007.02084
This paper addresses the task of estimating the 6 degrees of freedom pose of a known 3D object from depth information represented by a point cloud. Deep features learned by convolutional neural networks from color information have been the dominant f
Externí odkaz:
http://arxiv.org/abs/2001.08942
Decentralized policies for information gathering are required when multiple autonomous agents are deployed to collect data about a phenomenon of interest without the ability to communicate. Decentralized partially observable Markov decision processes
Externí odkaz:
http://arxiv.org/abs/1902.09840
Objects of different classes can be described using a limited number of attributes such as color, shape, pattern, and texture. Learning to detect object attributes instead of only detecting objects can be helpful in dealing with a priori unknown obje
Externí odkaz:
http://arxiv.org/abs/1811.04309
Rotation estimation of known rigid objects is important for robotic applications such as dexterous manipulation. Most existing methods for rotation estimation use intermediate representations such as templates, global or local feature descriptors, or
Externí odkaz:
http://arxiv.org/abs/1808.05498
We propose a new saliency-guided method for generating supervoxels in 3D space. Rather than using an evenly distributed spatial seeding procedure, our method uses visual saliency to guide the process of supervoxel generation. This results in densely
Externí odkaz:
http://arxiv.org/abs/1704.04054