108 citations · 109 across the 8 of their papers we have counts for
8 papers · 1 filter
Decision-Aware Attention Propagation for Vision Transformer Explainability
Sehyeong Jo, Gangjae Jang, Haesol Park
Vision Transformers (ViTs) have become a dominant architecture in computer vision, yet their prediction process remains difficult to interpret because information is propagated thr…
GMAR: Gradient-Driven Multi-Head Attention Rollout for Vision Transformer Interpretability
Sehyeong Jo, Gangjae Jang, Haesol Park
The Vision Transformer (ViT) has made significant advancements in computer vision, utilizing self-attention mechanisms to achieve state-of-the-art performance across various tasks,…
V-NAW: Video-based Noise-aware Adaptive Weighting for Facial Expression Recognition
JunGyu Lee, Kunyoung Lee, Haesol Park +2
Facial Expression Recognition (FER) plays a crucial role in human affective analysis and has been widely applied in computer vision tasks such as human-computer interaction and psy…
MAIR++: Improving Multi-view Attention Inverse Rendering with Implicit Lighting Representation
JunYong Choi, SeokYeong Lee, Haesol Park +3
In this paper, we propose a scene-level inverse rendering framework that uses multi-view images to decompose the scene into geometry, SVBRDF, and 3D spatially-varying lighting. Whi…
IG-FIQA: Improving Face Image Quality Assessment through Intra-class Variance Guidance robust to Inaccurate Pseudo-Labels
Minsoo Kim, Gi Pyo Nam, Haksub Kim +2
In the realm of face image quality assesment (FIQA), method based on sample relative classification have shown impressive performance. However, the quality scores used as pseudo-la…
MAIR: Multi-view Attention Inverse Rendering with 3D Spatially-Varying Lighting Estimation
JunYong Choi, SeokYeong Lee, Haesol Park +3
We propose a scene-level inverse rendering framework that uses multi-view images to decompose the scene into geometry, a SVBRDF, and 3D spatially-varying lighting. Because multi-vi…