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Workshop: Gaze Meets ML
EG-SIF: Improving Appearance Based Gaze Estimation using Self Improving Features
Vasudev Singh · Chaitanya Langde · Sourav Lakhotia · Vignesh Kannan · Shuaib Ahmed
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presentation:
Gaze Meets ML
Sat 16 Dec 6:15 a.m. PST — 3 p.m. PST
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OpenReview]
Sat 16 Dec 9 a.m. PST
— 9:15 a.m. PST
Sat 16 Dec 6:15 a.m. PST — 3 p.m. PST
Abstract:
Gaze estimation is vital in various applications, but factors like poor lighting and lowresolution images challenge the performance of estimation model. We introduce, for thefirst time a Eye Gaze Estimation with Self-Improving Features (EG-SIF) method. EG-SIFsegregates images based on their quality, generates a pair of good and adverse images, andapplies multitask training with image enhancement using the generated pairs, where thetask is to reconstruct given a poor image. This innovative approach outperforms existingmethods, significantly improving gaze estimation angular error on challenging datasets likeMPIIGaze from 4.64 to 4.53 and in RTGene from 7.44 to 7.41.
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