1 citations · 1 across the 4 of their papers we have counts for
7 papers
Training-Free Semantic Multi-Object Tracking with Vision-Language Models
Laurence Bonat, Francesco Tonini, Elisa Ricci +1
Semantic Multi-Object Tracking (SMOT) extends multi-object tracking with semantic outputs such as video summaries, instance-level captions, and interaction labels, aiming to move f…
Towards Unconstrained Human-Object Interaction
Francesco Tonini, Alessandro Conti, Lorenzo Vaquero +2
Human-Object Interaction (HOI) detection is a longstanding computer vision problem concerned with predicting the interaction between humans and objects. Current HOI models rely on…
Organizing Unstructured Image Collections using Natural Language
Mingxuan Liu, Zhun Zhong, Jun Li +3
In this work, we introduce and study the novel task of Open-ended Semantic Multiple Clustering (OpenSMC). Given a large, unstructured image collection, the goal is to automatically…
UrbanVerse: Scaling Urban Simulation by Watching City-Tour Videos
Mingxuan Liu, Honglin He, Elisa Ricci +2
Urban embodied AI agents, ranging from delivery robots to quadrupeds, are increasingly populating our cities, navigating chaotic streets to provide last-mile connectivity. Training…
Superpowering Open-Vocabulary Object Detectors for X-ray Vision
Pablo Garcia-Fernandez, Lorenzo Vaquero, Mingxuan Liu +5
Open-vocabulary object detection (OvOD) is set to revolutionize security screening by enabling systems to recognize any item in X-ray scans. However, developing effective OvOD mode…
Test-time Vocabulary Adaptation for Language-driven Object Detection
Mingxuan Liu, Tyler L. Hayes, Massimiliano Mancini +3
Open-vocabulary object detection models allow users to freely specify a class vocabulary in natural language at test time, guiding the detection of desired objects. However, vocabu…