1 citations · 1 across the 5 of their papers we have counts for
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GazeDiT: Gaze-Accurate Diffusion Image Generation for Eye Tracking via Spatial Conditioning
Dongze Wu, David Colmenares, Fengting Yang +4
Diffusion models are increasingly used to generate synthetic training data, but precise label control remains difficult when the conditioning signal is low-dimensional and coarse.…
GazePrior: Zero-Shot AR/VR Eye Tracking via Learned 3D Gaze Reconstruction
Corentin Dumery, David Colmenares, Alexander Fix +3
Eye tracking (ET) is a foundational technology for advanced AR/VR applications. However, training ET models for every new ET device is challenging: real data collection is costly a…
Rapidly deploying on-device eye tracking by distilling visual foundation models
Cheng Jiang, Jogendra Kundu, David Colmenares +4
Eye tracking (ET) plays a critical role in augmented and virtual reality applications. However, rapidly deploying high-accuracy, on-device gaze estimation for new products remains…
Polarization-resolved imaging improves eye tracking
Mantas Žurauskas, Tom Bu, Sanaz Alali +10
Polarization-resolved near-infrared imaging adds a useful optical contrast mechanism to eye tracking by measuring the polarization state of light reflected by ocular tissues in add…
Self-training of Machine Learning Models for Liver Histopathology: Generalization under Clinical Shifts
Jin Li, Deepta Rajan, Chintan Shah +7
Histopathology images are gigapixel-sized and include features and information at different resolutions. Collecting annotations in histopathology requires highly specialized pathol…