Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Almazan, Jon"'
Autor:
Foster, Thomas, Croitoru, Ioana, Dorfman, Robert, Edlund, Christoffer, Varsavsky, Thomas, Almazán, Jon
In this work, we address in-context learning (ICL) for the task of image segmentation, introducing a novel approach that adapts a modern Video Object Segmentation (VOS) technique for visual in-context learning. This adaptation is inspired by the VOS
Externí odkaz:
http://arxiv.org/abs/2312.06592
Strong image search models can be learned for a specific domain, ie. set of labels, provided that some labeled images of that domain are available. A practical visual search model, however, should be versatile enough to solve multiple retrieval tasks
Externí odkaz:
http://arxiv.org/abs/2210.02254
Dimensionality reduction methods are unsupervised approaches which learn low-dimensional spaces where some properties of the initial space, typically the notion of "neighborhood", are preserved. Such methods usually require propagation on large k-NN
Externí odkaz:
http://arxiv.org/abs/2110.09455
Image retrieval can be formulated as a ranking problem where the goal is to order database images by decreasing similarity to the query. Recent deep models for image retrieval have outperformed traditional methods by leveraging ranking-tailored loss
Externí odkaz:
http://arxiv.org/abs/1906.07589
Training a deep architecture using a ranking loss has become standard for the person re-identification task. Increasingly, these deep architectures include additional components that leverage part detections, attribute predictions, pose estimators an
Externí odkaz:
http://arxiv.org/abs/1801.05339
While deep learning has become a key ingredient in the top performing methods for many computer vision tasks, it has failed so far to bring similar improvements to instance-level image retrieval. In this article, we argue that reasons for the underwh
Externí odkaz:
http://arxiv.org/abs/1610.07940
We propose a novel approach for instance-level image retrieval. It produces a global and compact fixed-length representation for each image by aggregating many region-wise descriptors. In contrast to previous works employing pre-trained deep networks
Externí odkaz:
http://arxiv.org/abs/1604.01325
In this article we study the problem of document image representation based on visual features. We propose a comprehensive experimental study that compares three types of visual document image representations: (1) traditional so-called shallow featur
Externí odkaz:
http://arxiv.org/abs/1603.01076
The goal of this work is to bring semantics into the tasks of text recognition and retrieval in natural images. Although text recognition and retrieval have received a lot of attention in recent years, previous works have focused on recognizing or re
Externí odkaz:
http://arxiv.org/abs/1509.06243
Publikováno v:
In Pattern Recognition December 2014 47(12):3967-3978
