AI That Fixes Your Eye Contact in Photos—No Labels Needed
Look me in the eye, camera.
Ever snapped a great photo except your eyes aren’t on the camera? This research introduces GazeCorrection, an AI that subtly redirects your gaze by re-synthesizing just the eye region—keeping your identity and expression intact.
How it works: a self-supervised generative model treats gaze editing like smart inpainting. Instead of needing labeled head poses or eye angles, it learns from unlabeled face images to fill in the “missing” eye area with a corrected, forward-looking gaze. A self-guided pretraining step helps the model capture angle-invariant features, so results look natural “in the wild” (photos scraped from the web).
- Label-free training data
- Identity-preserving edits
- Compelling results on diverse, real-world images
Use cases span video calls, group photos, accessibility, and content creation. As with any face-editing tech, ethical, consent-based use is essential.
Paper: arxiv.org/abs/1906.00805 • Code: github.com/zhangqianhui/GazeCorrection
Paper: http://arxiv.org/abs/1906.00805v1
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AI ComputerVision GAN GazeCorrection EyeContact Inpainting SelfSupervised Research OpenSource Ethics
