7 citations · 7 across the 17 of their papers we have counts for
18 papers
RankAlign: Vision-Language Representation Alignment via Rank Transformation
Enzhe Zhao, Marco Fiorucci, Lamberto Ballan
While the Platonic Representation Hypothesis posits that vision and language models converge toward compatible latent geometries, recovering class-level correspondences between unp…
XiDepth: a Lightweight and Efficient Network for Self-supervised Monocular Depth Estimation
Elena Izzo, Riccardo Toniolo, Lamberto Ballan
Self-supervised monocular depth estimation has emerged as an appealing solution to design lightweight and effective models for deployment on computationally constrained devices due…
IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation
Jelin Raphael Akkara, Filippo Ziliotto, Luciano Serafini +2
Embodied AI increasingly relies on queryable semantic maps built from pre-trained vision-language models to enable zero-shot Object Goal Navigation (ObjectNav). However, existing a…
What VGGT Knows About Overlap: Probing Geometric Foundation Models for Co-Visibility
Filippo Ziliotto, Luciano Serafini, Lamberto Ballan +1
A fundamental challenge in 3D reconstruction and robotic localization is co-visibility: determining which image pairs share overlapping visible surfaces, particularly in scenarios…
You Only Landmark Once: Lightweight U-Net Face Super Resolution with YOLO-World Landmark Heatmaps
Riccardo Carraro, Anna Briotto, Endi Hysa +2
Face image super-resolution aims to recover high-resolution facial images from severely degraded inputs. Under extreme upscaling factors, fine facial details are often lost, making…
Contrastive Learning under Noisy Temporal Self-Supervision for Colonoscopy Videos
Luca Parolari, Pietro Gori, Lamberto Ballan +2
Learning robust representations of polyp tracklets is key to enabling multiple AI-assisted colonoscopy applications, from polyp characterization to automated reporting and retrieva…
Benchmarking Layout-Guided Diffusion Models through Unified Semantic-Spatial Evaluation in Closed and Open Settings
Luca Parolari, Nicla Faccioli, Lamberto Ballan
Evaluating layout-guided text-to-image generative models requires assessing both semantic alignment with textual prompts and spatial fidelity to prescribed layouts. Assessing layou…
Multiview Progress Prediction of Robot Activities
Elena Zoppellari, Federico Becattini, Marco Fiorucci +1
For robots to operate effectively and safely alongside humans, they must be able to understand the progress of ongoing actions. This ability, known as action progress prediction, i…
Assessing the Visual Enumeration Abilities of Specialized Counting Architectures and Vision-Language Models
Kuinan Hou, Jing Mi, Marco Zorzi +2
Counting the number of items in a visual scene remains a fundamental yet challenging task in computer vision. Traditional approaches to solving this problem rely on domain-specific…
PersONAL: Towards a Comprehensive Benchmark for Personalized Embodied Agents
Filippo Ziliotto, Jelin Raphael Akkara, Alessandro Daniele +3
Recent advances in Embodied AI have enabled agents to perform increasingly complex tasks and adapt to diverse environments. However, deploying such agents in realistic human-center…
7Bench: a Comprehensive Benchmark for Layout-guided Text-to-image Models
Elena Izzo, Luca Parolari, Davide Vezzaro +1
Layout-guided text-to-image models offer greater control over the generation process by explicitly conditioning image synthesis on the spatial arrangement of elements. As a result,…
Temporally-Aware Supervised Contrastive Learning for Polyp Counting in Colonoscopy
Luca Parolari, Andrea Cherubini, Lamberto Ballan +1
Automated polyp counting in colonoscopy is a crucial step toward automated procedure reporting and quality control, aiming to enhance the cost-effectiveness of colonoscopy screenin…
MLFM: Multi-Layered Feature Maps for Richer Language Understanding in Zero-Shot Semantic Navigation
Sonia Raychaudhuri, Enrico Cancelli, Tommaso Campari +3
Recent progress in large vision-language models has driven improvements in language-based semantic navigation, where an embodied agent must reach a target object described in natur…
Towards Polyp Counting In Full-Procedure Colonoscopy Videos
Luca Parolari, Andrea Cherubini, Lamberto Ballan +1
Automated colonoscopy reporting holds great potential for enhancing quality control and improving cost-effectiveness of colonoscopy procedures. A major challenge lies in the automa…
TANGO: Training-free Embodied AI Agents for Open-world Tasks
Filippo Ziliotto, Tommaso Campari, Luciano Serafini +1
Large Language Models (LLMs) have demonstrated excellent capabilities in composing various modules together to create programs that can perform complex reasoning tasks on images. I…
Harlequin: Color-driven Generation of Synthetic Data for Referring Expression Comprehension
Luca Parolari, Elena Izzo, Lamberto Ballan
Referring Expression Comprehension (REC) aims to identify a particular object in a scene by a natural language expression, and is an important topic in visual language understandin…
FastSTI: A Fast Conditional Pseudo Numerical Diffusion Model for Spatio-temporal Traffic Data Imputation
Shaokang Cheng, Nada Osman, Shiru Qu +1
High-quality spatiotemporal traffic data is crucial for intelligent transportation systems (ITS) and their data-driven applications. Inevitably, the issue of missing data caused by…
Following the Human Thread in Social Navigation
Luca Scofano, Alessio Sampieri, Tommaso Campari +4
The success of collaboration between humans and robots in shared environments relies on the robot's real-time adaptation to human motion. Specifically, in Social Navigation, the ag…