5 papers
FineBench: Benchmarking and Enhancing Vision-Language Models for Fine-grained Human Activity Understanding
Gueter Josmy Faure, Min-Hung Chen, Jia-Fong Yeh +2
Vision-Language Models (VLMs) have demonstrated remarkable capabilities in general video understanding, yet they often struggle with the fine-grained comprehension crucial for real…
SPATIOROUTE: Dynamic Prompt Routing for Zero-Shot Spatial Reasoning
Pawat Chunhachatrachai, Gueter Josmy Faure, Hung-Ting Su +1
Spatial question answering over egocentric video is a challenging task that requires Vision-Language Models (VLMs) to reason about 3D object positions, scene affordances, and direc…
SceneFunRI: Reasoning the Invisible for Task-Driven Functional Object Localization
Posheng Chen, Powen Cheng, Gueter Josmy Faure +2
In real-world scenes, target objects may reside in regions that are not visible. While humans can often infer the locations of occluded objects from context and commonsense knowled…
MovieCORE: COgnitive REasoning in Movies
Gueter Josmy Faure, Min-Hung Chen, Jia-Fong Yeh +5
This paper introduces MovieCORE, a novel video question answering (VQA) dataset designed to probe deeper cognitive understanding of movie content. Unlike existing datasets that foc…
HERMES: temporal-coHERent long-forM understanding with Episodes and Semantics
Gueter Josmy Faure, Jia-Fong Yeh, Min-Hung Chen +3
Long-form video understanding presents unique challenges that extend beyond traditional short-video analysis approaches, particularly in capturing long-range dependencies, processi…