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20242026
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cs.CV2026

Memory-Augmented Vision-Language Agents for Persistent and Semantically Consistent Object Captioning

Tommaso Galliena, Stefano Rosa, Tommaso Apicella +3

Vision-Language Models (VLMs) often yield inconsistent descriptions of the same object across viewpoints, hindering the ability of embodied agents to construct consistent semantic…

cs.CV2025

CloseUpAvatar: High-Fidelity Animatable Full-Body Avatars with Mixture of Multi-Scale Textures

David Svitov, Pietro Morerio, Lourdes Agapito +1

We present a CloseUpAvatar - a novel approach for articulated human avatar representation dealing with more general camera motions, while preserving rendering quality for close-up…

cs.CV2025

E-M3RF: An Equivariant Multimodal 3D Re-assembly Framework

Adeela Islam, Stefano Fiorini, Manuel Lecha +4

3D reassembly is a fundamental geometric problem, and in recent years it has increasingly been challenged by deep learning methods rather than classical optimization. While learnin…

cs.CV2025

ReassembleNet: Learnable Keypoints and Diffusion for 2D Fresco Reconstruction

Adeela Islam, Stefano Fiorini, Stuart James +2

The task of reassembly is a significant challenge across multiple domains, including archaeology, genomics, and molecular docking, requiring the precise placement and orientation o…

cs.CV2025

A Mutual Information Perspective on Multiple Latent Variable Generative Models for Positive View Generation

Dario Serez, Marco Cristani, Alessio Del Bue +2

In image generation, Multiple Latent Variable Generative Models (MLVGMs) employ multiple latent variables to gradually shape the final images, from global characteristics to finer…

cs.CV2025

Embodied Image Captioning: Self-supervised Learning Agents for Spatially Coherent Image Descriptions

Tommaso Galliena, Tommaso Apicella, Stefano Rosa +3

We present a self-supervised method to improve an agent's abilities in describing arbitrary objects while actively exploring a generic environment. This is a challenging problem, a…