42 citations · 57 across the 14 of their papers we have counts for
12 papers · 1 filter
Reproducible Multimodal Affordance Prediction
Tommaso Apicella, Alessio Xompero, Andrea Cavallaro
Affordance prediction is the identification of potential actions an agent can perform on a target object from multimodal inputs. Affordance prediction methods are difficult to eval…
On the Robustness of Vision-Language Models in Zero-shot Privacy Classification
Alina Elena Baia, Alessio Xompero, Andrea Cavallaro
Automatic systems for document understanding require multimodal models that accurately identify sensitive visual content, even in the presence of image degradations. Instruction-fo…
Visual Affordance Prediction: Survey and Reproducibility
Tommaso Apicella, Alessio Xompero, Andrea Cavallaro
Affordances are the potential actions an agent can perform on an object, as observed by a camera. Visual affordance prediction is formulated differently for tasks such as grasping…
Learning Privacy from Visual Entities
Alessio Xompero, Andrea Cavallaro
Subjective interpretation and content diversity make predicting whether an image is private or public a challenging task. Graph neural networks combined with convolutional neural n…
Segmenting Object Affordances: Reproducibility and Sensitivity to Scale
Tommaso Apicella, Alessio Xompero, Paolo Gastaldo +1
Visual affordance segmentation identifies image regions of an object an agent can interact with. Existing methods re-use and adapt learning-based architectures for semantic segment…
Explaining models relating objects and privacy
Alessio Xompero, Myriam Bontonou, Jean-Michel Arbona +2
Accurately predicting whether an image is private before sharing it online is difficult due to the vast variety of content and the subjective nature of privacy itself. In this pape…
Affordance segmentation of hand-occluded containers from exocentric images
Tommaso Apicella, Alessio Xompero, Edoardo Ragusa +3
Visual affordance segmentation identifies the surfaces of an object an agent can interact with. Common challenges for the identification of affordances are the variety of the geome…
A mixed-reality dataset for category-level 6D pose and size estimation of hand-occluded containers
Xavier Weber, Alessio Xompero, Andrea Cavallaro
Estimating the 6D pose and size of household containers is challenging due to large intra-class variations in the object properties, such as shape, size, appearance, and transparen…
Cross-Camera View-Overlap Recognition
Alessio Xompero, Andrea Cavallaro
We propose a decentralised view-overlap recognition framework that operates across freely moving cameras without the need of a reference 3D map. Each camera independently extracts,…
Improving filling level classification with adversarial training
Apostolos Modas, Alessio Xompero, Ricardo Sanchez-Matilla +2
We investigate the problem of classifying - from a single image - the level of content in a cup or a drinking glass. This problem is made challenging by several ambiguities caused…
Multi-view shape estimation of transparent containers
Alessio Xompero, Ricardo Sanchez-Matilla, Apostolos Modas +2
The 3D localisation of an object and the estimation of its properties, such as shape and dimensions, are challenging under varying degrees of transparency and lighting conditions.…
An On-line Variational Bayesian Model for Multi-Person Tracking from Cluttered Scenes
Sileye Ba, Xavier Alameda-Pineda, Alessio Xompero +1
Object tracking is an ubiquitous problem that appears in many applications such as remote sensing, audio processing, computer vision, human-machine interfaces, human-robot interact…