MPIIGaze: Real-World Dataset and Deep Appearance-Based Gaze Estimation

Understand

Learning-based methods are believed to work well for unconstrained gaze estimation, i.e.

• gaze estimation from a monocular RGB camera without assumptions regarding user, environment, or camera.
• However, current gaze datasets were collected under laboratory conditions and methods were not evaluated across multiple datasets.
• Our work makes three contributions towards addressing these limitations.