Zobrazeno 1 - 10
of 77
pro vyhledávání: '"De Nadai, Marco"'
Generative retrieval for search and recommendation is a promising paradigm for retrieving items, offering an alternative to traditional methods that depend on external indexes and nearest-neighbor searches. Instead, generative models directly associa
Externí odkaz:
http://arxiv.org/abs/2410.16823
In today's interconnected world of widespread mobility, ubiquitous social interaction, and rapid information dissemination, the demand for individuals to swiftly adapt their behaviors has increased dramatically. Timely decision-making faces new chall
Externí odkaz:
http://arxiv.org/abs/2403.10276
Autor:
Damianou, Andreas, Fabbri, Francesco, Gigioli, Paul, De Nadai, Marco, Wang, Alice, Palumbo, Enrico, Lalmas, Mounia
In the realm of personalization, integrating diverse information sources such as consumption signals and content-based representations is becoming increasingly critical to build state-of-the-art solutions. In this regard, two of the biggest trends in
Externí odkaz:
http://arxiv.org/abs/2403.07478
Autor:
De Nadai, Marco, Fabbri, Francesco, Gigioli, Paul, Wang, Alice, Li, Ang, Silvestri, Fabrizio, Kim, Laura, Lin, Shawn, Radosavljevic, Vladan, Ghael, Sandeep, Nyhan, David, Bouchard, Hugues, Lalmas-Roelleke, Mounia, Damianou, Andreas
In the ever-evolving digital audio landscape, Spotify, well-known for its music and talk content, has recently introduced audiobooks to its vast user base. While promising, this move presents significant challenges for personalized recommendations. U
Externí odkaz:
http://arxiv.org/abs/2403.05185
Autor:
Liu, Yahui, Sangineto, Enver, Chen, Yajing, Bao, Linchao, Zhang, Haoxian, Sebe, Nicu, Lepri, Bruno, De Nadai, Marco
Multi-domain image-to-image (I2I) translations can transform a source image according to the style of a target domain. One important, desired characteristic of these transformations, is their graduality, which corresponds to a smooth change between t
Externí odkaz:
http://arxiv.org/abs/2210.00841
Autor:
Peruzzo, Elia, Sangineto, Enver, Liu, Yahui, De Nadai, Marco, Bi, Wei, Lepri, Bruno, Sebe, Nicu
Recent work on Vision Transformers (VTs) showed that introducing a local inductive bias in the VT architecture helps reducing the number of samples necessary for training. However, the architecture modifications lead to a loss of generality of the Tr
Externí odkaz:
http://arxiv.org/abs/2206.04636
Publikováno v:
IEEE Transactions on Multimedia, 2022
Recently, there has been an increasing interest in image editing methods that employ pre-trained unconditional image generators (e.g., StyleGAN). However, applying these methods to translate images to multiple visual domains remains challenging. Exis
Externí odkaz:
http://arxiv.org/abs/2109.12492
This paper introduces Click to Move (C2M), a novel framework for video generation where the user can control the motion of the synthesized video through mouse clicks specifying simple object trajectories of the key objects in the scene. Our model rec
Externí odkaz:
http://arxiv.org/abs/2108.08815
Autor:
Lucchini, Lorenzo, Centellegher, Simone, Pappalardo, Luca, Gallotti, Riccardo, Privitera, Filippo, Lepri, Bruno, De Nadai, Marco
The non-pharmaceutical interventions (NPIs), aimed at reducing the diffusion of the COVID-19 pandemic, has dramatically influenced our behaviour in everyday life. In this work, we study how individuals adapted their daily movements and person-to-pers
Externí odkaz:
http://arxiv.org/abs/2107.12235
Autor:
Liu, Yahui, Sangineto, Enver, Chen, Yajing, Bao, Linchao, Zhang, Haoxian, Sebe, Nicu, Lepri, Bruno, Wang, Wei, De Nadai, Marco
Image-to-Image (I2I) multi-domain translation models are usually evaluated also using the quality of their semantic interpolation results. However, state-of-the-art models frequently show abrupt changes in the image appearance during interpolation, a
Externí odkaz:
http://arxiv.org/abs/2106.09016