Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Izadinia, Hamid"'
Nonprehensile manipulation involves long horizon underactuated object interactions and physical contact with different objects that can inherently introduce a high degree of uncertainty. In this work, we introduce a novel Real-to-Sim reward analysis
Externí odkaz:
http://arxiv.org/abs/2111.07986
Autor:
Izadinia, Hamid, Seitz, Steven M.
By moving a depth sensor around a room, we compute a 3D CAD model of the environment, capturing the room shape and contents such as chairs, desks, sofas, and tables. Rather than reconstructing geometry, we match, place, and align each object in the s
Externí odkaz:
http://arxiv.org/abs/1812.05583
Autor:
Izadinia, Hamid, Garrigues, Pierre
In this work, we propose the use of large set of unlabeled images as a source of regularization data for learning robust visual representation. Given a visual model trained by a labeled dataset in a supervised fashion, we augment our training samples
Externí odkaz:
http://arxiv.org/abs/1802.02568
Automated photo tagging has established itself as one of the most compelling applications of deep learning. While deep convolutional neural networks have repeatedly demonstrated top performance on standard datasets for classification, there are a num
Externí odkaz:
http://arxiv.org/abs/1612.01922
Given a single photo of a room and a large database of furniture CAD models, our goal is to reconstruct a scene that is as similar as possible to the scene depicted in the photograph, and composed of objects drawn from the database. We present a comp
Externí odkaz:
http://arxiv.org/abs/1608.05137
We introduce Segment-Phrase Table (SPT), a large collection of bijective associations between textual phrases and their corresponding segmentations. Leveraging recent progress in object recognition and natural language semantics, we show how we can s
Externí odkaz:
http://arxiv.org/abs/1509.08075
Autor:
Sadeghi, Fereshteh, Izadinia, Hamid
Word clouds and text visualization is one of the recent most popular and widely used types of visualizations. Despite the attractiveness and simplicity of producing word clouds, they do not provide a thorough visualization for the distribution of the
Externí odkaz:
http://arxiv.org/abs/1412.6079
This paper proposes direct learning of image classification from user-supplied tags, without filtering. Each tag is supplied by the user who shared the image online. Enormous numbers of these tags are freely available online, and they give insight ab
Externí odkaz:
http://arxiv.org/abs/1411.6909
Publikováno v:
In Pattern Recognition Letters 2011 32(12):1622-1634
Publikováno v:
In Neural Networks 2009 22(5):633-641