GMGaze achieves mean angular errors of 2.49°, 3.22°, 10.16°, and 1.44° on MPIIFaceGaze, EYEDIAP, Gaze360, and ETH-XGaze by early context-conditioned fusion and MoE scaling, outperforming baselines in within- and cross-domain settings.
Slyklatent: A learning framework for gaze estimation using deep facial feature learning.IEEE Transactions on Human-Machine Systems
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GMGaze: MoE-Based Context-Aware Gaze Estimation with CLIP and Multiscale Transformer
GMGaze achieves mean angular errors of 2.49°, 3.22°, 10.16°, and 1.44° on MPIIFaceGaze, EYEDIAP, Gaze360, and ETH-XGaze by early context-conditioned fusion and MoE scaling, outperforming baselines in within- and cross-domain settings.