BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//ITSERR - ECPv6.2.8.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.itserr.it
X-WR-CALDESC:Events for ITSERR
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Brussels
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20240331T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20241027T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;VALUE=DATE:20240929
DTEND;VALUE=DATE:20241005
DTSTAMP:20260416T030700
CREATED:20250310T122018Z
LAST-MODIFIED:20250310T144140Z
UID:1251-1727568000-1728086399@www.itserr.it
SUMMARY:Computer Vision - ECCV2024 18th European Conference
DESCRIPTION:Federico Cocchi and Marcella Cornia (University of Modena and Reggio Emilia) participated in the 18th European Conference on Computer Vision (ECCV 2024)\, presenting the paper “Safe-CLIP: Removing NSFW Concepts from Vision-and-Language Models.” \nThe study addresses the challenge of enhancing the safety of vision-and-language models\, such as CLIP\, by reducing their sensitivity to NSFW (not safe for work) inputs. The proposed approach “unlearns” unsafe concepts by fine-tuning the model on synthetically generated safe and unsafe data\, improving its reliability in sensitive and trustworthy contexts. The research demonstrates how this method can be effectively integrated with pre-trained generative models for safer applications.
URL:https://www.itserr.it/event/computer-vision-eccv2024-18th-european-conference/
LOCATION:MiCo\, Milan\, Italy
END:VEVENT
END:VCALENDAR