4 papers · 1 filter
Disentangled Concepts Speak Louder Than Words: Explainable Video Action Recognition
Jongseo Lee, Wooil Lee, Gyeong-Moon Park +2
Effective explanations of video action recognition models should disentangle how movements unfold over time from the surrounding spatial context. However, existing methods based on…
HERO-VQL: Hierarchical, Egocentric and Robust Visual Query Localization
Joohyun Chang, Soyeon Hong, Hyogun Lee +4
In this work, we tackle the egocentric visual query localization (VQL), where a model should localize the query object in a long-form egocentric video. Frequent and abrupt viewpoin…
PCBEAR: Pose Concept Bottleneck for Explainable Action Recognition
Jongseo Lee, Wooil Lee, Gyeong-Moon Park +2
Human action recognition (HAR) has achieved impressive results with deep learning models, but their decision-making process remains opaque due to their black-box nature. Ensuring i…
PCEvE: Part Contribution Evaluation Based Model Explanation for Human Figure Drawing Assessment and Beyond
Jongseo Lee, Geo Ahn, Seong Tae Kim +1
For automatic human figure drawing (HFD) assessment tasks, such as diagnosing autism spectrum disorder (ASD) using HFD images, the clarity and explainability of a model decision ar…