Zobrazeno 1 - 10
of 311
pro vyhledávání: '"Medioni, Gérard"'
With the increasing size of datasets used for training neural networks, data pruning becomes an attractive field of research. However, most current data pruning algorithms are limited in their ability to preserve accuracy compared to models trained o
Externí odkaz:
http://arxiv.org/abs/2403.07854
Autor:
Shoshan, Alon, Bhonker, Nadav, Baruch, Emanuel Ben, Nizan, Ori, Kviatkovsky, Igor, Engelsma, Joshua, Aggarwal, Manoj, Medioni, Gerard
Training fingerprint recognition models using synthetic data has recently gained increased attention in the biometric community as it alleviates the dependency on sensitive personal data. Existing approaches for fingerprint generation are limited in
Externí odkaz:
http://arxiv.org/abs/2310.19024
This paper presents Shape of You (SoY), an approach to improve the accuracy of 3D body shape estimation for vision-based clothing recommendation systems. While existing methods have successfully estimated 3D poses, there remains a lack of work in pre
Externí odkaz:
http://arxiv.org/abs/2304.07389
Recent advancements in Natural Language Processing (NLP) have led to the development of NLP-based recommender systems that have shown superior performance. However, current models commonly treat items as mere IDs and adopt discriminative modeling, re
Externí odkaz:
http://arxiv.org/abs/2304.03879
Autor:
Linial, Ori, Shoshan, Alon, Bhonker, Nadav, Hirsch, Elad, Zamir, Lior, Kviatkovsky, Igor, Medioni, Gerard
The asymmetrical retrieval setting is a well suited solution for resource constrained applications such as face recognition and image retrieval. In this setting, a large model is used for indexing the gallery while a lightweight model is used for que
Externí odkaz:
http://arxiv.org/abs/2303.17531
Autor:
Grosz, Steven A., Engelsma, Joshua J., Ranjan, Rajeev, Ramakrishnan, Naveen, Aggarwal, Manoj, Medioni, Gerard G., Jain, Anil K.
Minutiae matching has long dominated the field of fingerprint recognition. However, deep networks can be used to extract fixed-length embeddings from fingerprints. To date, the few studies that have explored the use of CNN architectures to extract su
Externí odkaz:
http://arxiv.org/abs/2210.13994
Autor:
Sevegnani, Karin, Seshadri, Arjun, Wang, Tian, Beniwal, Anurag, McAuley, Julian, Lu, Alan, Medioni, Gerard
Recommender systems and search are both indispensable in facilitating personalization and ease of browsing in online fashion platforms. However, the two tools often operate independently, failing to combine the strengths of recommender systems to acc
Externí odkaz:
http://arxiv.org/abs/2207.12033
Deep learning model inference on embedded devices is challenging due to the limited availability of computation resources. A popular alternative is to perform model inference on the cloud, which requires transmitting images from the embedded device t
Externí odkaz:
http://arxiv.org/abs/2204.10869
Autor:
Sarkar, Rohan, Bodla, Navaneeth, Vasileva, Mariya I., Lin, Yen-Liang, Beniwal, Anurag, Lu, Alan, Medioni, Gerard
Learning an effective outfit-level representation is critical for predicting the compatibility of items in an outfit, and retrieving complementary items for a partial outfit. We present a framework, OutfitTransformer, that uses the proposed task-spec
Externí odkaz:
http://arxiv.org/abs/2204.04812
Autor:
Wu, Jialian, Yarram, Sudhir, Liang, Hui, Lan, Tian, Yuan, Junsong, Eledath, Jayan, Medioni, Gerard
Video Instance Segmentation (VIS) aims to simultaneously classify, segment, and track multiple object instances in videos. Recent clip-level VIS takes a short video clip as input each time showing stronger performance than frame-level VIS (tracking-b
Externí odkaz:
http://arxiv.org/abs/2203.01853