39 citations · 46 across the 20 of their papers we have counts for
8 papers · 1 filter
DreamCache: Finetuning-Free Lightweight Personalized Image Generation via Feature Caching
Emanuele Aiello, Umberto Michieli, Diego Valsesia +2
Personalized image generation requires text-to-image generative models that capture the core features of a reference subject to allow for controlled generation across different con…
Swiss DINO: Efficient and Versatile Vision Framework for On-device Personal Object Search
Kirill Paramonov, Jia-Xing Zhong, Umberto Michieli +2
In this paper, we address a recent trend in robotic home appliances to include vision systems on personal devices, capable of personalizing the appliances on the fly. In particular…
Enhanced Model Robustness to Input Corruptions by Per-corruption Adaptation of Normalization Statistics
Elena Camuffo, Umberto Michieli, Simone Milani +2
Developing a reliable vision system is a fundamental challenge for robotic technologies (e.g., indoor service robots and outdoor autonomous robots) which can ensure reliable naviga…
Cross-Architecture Auxiliary Feature Space Translation for Efficient Few-Shot Personalized Object Detection
Francesco Barbato, Umberto Michieli, Jijoong Moon +2
Recent years have seen object detection robotic systems deployed in several personal devices (e.g., home robots and appliances). This has highlighted a challenge in their design, i…
Object-conditioned Bag of Instances for Few-Shot Personalized Instance Recognition
Umberto Michieli, Jijoong Moon, Daehyun Kim +1
Nowadays, users demand for increased personalization of vision systems to localize and identify personal instances of objects (e.g., my dog rather than dog) from a few-shot dataset…
A Modular System for Enhanced Robustness of Multimedia Understanding Networks via Deep Parametric Estimation
Francesco Barbato, Umberto Michieli, Mehmet Kerim Yucel +2
In multimedia understanding tasks, corrupted samples pose a critical challenge, because when fed to machine learning models they lead to performance degradation. In the past, three…