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Unsupervised Gaze-aware Contrastive Learning with Subject-specific Condition
Appearance-based gaze estimation has shown great promise in many applications by using a single general-purpose camera as the input device.
FreeGaze: Resource-efficient Gaze Estimation via Frequency Domain Contrastive Learning
The former significantly alleviates the computational burden in both system calibration and gaze estimation, and dramatically reduces the system latency; while the latter overcomes the data labeling hurdle of existing supervised learning-based counterparts, and ensures efficient gaze representation learning in the absence of gaze label.
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