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cs.CV2026
GMGaze: MoE-Based Context-Aware Gaze Estimation with CLIP and Multiscale Transformer
Xinyuan Zhao, Yihang Wu, Ahmad Chaddad +2
Gaze estimation methods commonly use facial appearances to predict the direction of a person gaze. However, previous studies show three major challenges with convolutional neural n…
cs.CV2026
Federated Vision Transformer with Adaptive Focal Loss for Medical Image Classification
Xinyuan Zhao, Yihang Wu, Ahmad Chaddad +2
While deep learning models like Vision Transformer (ViT) have achieved significant advances, they typically require large datasets. With data privacy regulations, access to many or…
cs.CV2026
GazeFormer-MoE: Context-Aware Gaze Estimation via CLIP and MoE Transformer
Xinyuan Zhao, Xianrui Chen, Ahmad Chaddad
We present a semantics modulated, multi scale Transformer for 3D gaze estimation. Our model conditions CLIP global features with learnable prototype banks (illumination, head pose,…