3 papers
cs.CV2025
Comprehensive Information Bottleneck for Unveiling Universal Attribution to Interpret Vision Transformers
Jung-Ho Hong, Ho-Joong Kim, Kyu-Sung Jeon +1
The feature attribution method reveals the contribution of input variables to the decision-making process to provide an attribution map for explanation. Existing methods grounded o…
cs.CV2025
Towards Better Visualizing the Decision Basis of Networks via Unfold and Conquer Attribution Guidance
Jung-Ho Hong, Woo-Jeoung Nam, Kyu-Sung Jeon +1
Revealing the transparency of Deep Neural Networks (DNNs) has been widely studied to describe the decision mechanisms of network inner structures. In this paper, we propose a novel…
cs.CV2025
DiGIT: Multi-Dilated Gated Encoder and Central-Adjacent Region Integrated Decoder for Temporal Action Detection Transformer
Ho-Joong Kim, Yearang Lee, Jung-Ho Hong +1
In this paper, we examine a key limitation in query-based detectors for temporal action detection (TAD), which arises from their direct adaptation of originally designed architectu…