17 citations · 53 across the 11 of their papers we have counts for
15 papers
ImageRAGTurbo: Towards One-step Text-to-Image Generation with Retrieval-Augmented Diffusion Models
Peijie Qiu, Hariharan Ramshankar, Arnau Ramisa +4
Diffusion models have emerged as the leading approach for text-to-image generation. However, their iterative sampling process, which gradually morphs random noise into coherent ima…
Recommendation with Generative Models
Yashar Deldjoo, Zhankui He, Julian McAuley +8
Generative models are a class of AI models capable of creating new instances of data by learning and sampling from their statistical distributions. In recent years, these models ha…
Multi-modal Generative Models in Recommendation System
Arnau Ramisa, Rene Vidal, Yashar Deldjoo +8
Many recommendation systems limit user inputs to text strings or behavior signals such as clicks and purchases, and system outputs to a list of products sorted by relevance. With t…
Large Language Model Driven Recommendation
Anton Korikov, Scott Sanner, Yashar Deldjoo +8
While previous chapters focused on recommendation systems (RSs) based on standardized, non-verbal user feedback such as purchases, views, and clicks -- the advent of LLMs has unloc…
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)
Yashar Deldjoo, Zhankui He, Julian McAuley +7
Traditional recommender systems (RS) typically use user-item rating histories as their main data source. However, deep generative models now have the capability to model and sample…
On Utilizing Relationships for Transferable Few-Shot Fine-Grained Object Detection
Ambar Pal, Arnau Ramisa, Amit Kumar K C +1
State-of-the-art object detectors are fast and accurate, but they require a large amount of well annotated training data to obtain good performance. However, obtaining a large amou…
A Review of Modern Fashion Recommender Systems
Yashar Deldjoo, Fatemeh Nazary, Arnau Ramisa +4
The textile and apparel industries have grown tremendously over the last few years. Customers no longer have to visit many stores, stand in long queues, or try on garments in dress…
Main Product Detection with Graph Networks for Fashion
Vacit Oguz Yazici, Longlong Yu, Arnau Ramisa +2
Computer vision has established a foothold in the online fashion retail industry. Main product detection is a crucial step of vision-based fashion product feed parsing pipelines, f…
T-VSE: Transformer-Based Visual Semantic Embedding
Muhammet Bastan, Arnau Ramisa, Mehmet Tek
Transformer models have recently achieved impressive performance on NLP tasks, owing to new algorithms for self-supervised pre-training on very large text corpora. In contrast, rec…
Orderless Recurrent Models for Multi-label Classification
Vacit Oguz Yazici, Abel Gonzalez-Garcia, Arnau Ramisa +2
Recurrent neural networks (RNN) are popular for many computer vision tasks, including multi-label classification. Since RNNs produce sequential outputs, labels need to be ordered f…
Learning Metrics from Teachers: Compact Networks for Image Embedding
Lu Yu, Vacit Oguz Yazici, Xialei Liu +3
Metric learning networks are used to compute image embeddings, which are widely used in many applications such as image retrieval and face recognition. In this paper, we propose to…
Visually-Aware Personalized Recommendation using Interpretable Image Representations
Charles Packer, Julian McAuley, Arnau Ramisa
Visually-aware recommender systems use visual signals present in the underlying data to model the visual characteristics of items and users' preferences towards them. In the domain…
BreakingNews: Article Annotation by Image and Text Processing
Arnau Ramisa, Fei Yan, Francesc Moreno-Noguer +1
Building upon recent Deep Neural Network architectures, current approaches lying in the intersection of computer vision and natural language processing have achieved unprecedented…
Structured Prediction with Output Embeddings for Semantic Image Annotation
Ariadna Quattoni, Arnau Ramisa, Pranava Swaroop Madhyastha +2
We address the task of annotating images with semantic tuples. Solving this problem requires an algorithm which is able to deal with hundreds of classes for each argument of the tu…
Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot
Arnau Ramisa, David Aldavert, Shrihari Vasudevan +2
This paper addresses object perception applied to mobile robotics. Being able to perceive semantically meaningful objects in unstructured environments is a key capability in order…