3 papers
cs.CV2026
Large Multimodal Models as General In-Context Classifiers
Marco Garosi, Matteo Farina, Alessandro Conti +2
Which multimodal model should we use for classification? Previous studies suggest that the answer lies in CLIP-like contrastive Vision-Language Models (VLMs), due to their remarkab…
cs.CV2025
Compositional Caching for Training-free Open-vocabulary Attribute Detection
Marco Garosi, Alessandro Conti, Gaowen Liu +2
Attribute detection is crucial for many computer vision tasks, as it enables systems to describe properties such as color, texture, and material. Current approaches often rely on l…
cs.CV2025
3D Part Segmentation via Geometric Aggregation of 2D Visual Features
Marco Garosi, Riccardo Tedoldi, Davide Boscaini +3
Supervised 3D part segmentation models are tailored for a fixed set of objects and parts, limiting their transferability to open-set, real-world scenarios. Recent works have explor…