A hardware prototype performs gaze estimation by optically encoding task-relevant features with a microlens array and mask, captured on a 4x4 phototransistor array and decoded by a small neural network, reaching 3.4 ms latency with competitive accuracy.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
verdicts
UNVERDICTED 3representative citing papers
DISCA achieves 3.59 TOPS/W per bit energy efficiency for matrix multiplication at 500 MHz in 180 nm CMOS using a compressed Bent-Pyramid stochastic format.
Extends unsupervised eye contact detection for mobile scenarios, reporting significant performance gains on two datasets and new attention metrics.
citing papers explorer
-
Low Latency Gaze Tracking via Latent Optical Sensing
A hardware prototype performs gaze estimation by optically encoding task-relevant features with a microlens array and mask, captured on a 4x4 phototransistor array and decoded by a small neural network, reaching 3.4 ms latency with competitive accuracy.
-
DISCA: A Digital In-memory Stochastic Computing Architecture Using A Compressed Bent-Pyramid Format
DISCA achieves 3.59 TOPS/W per bit energy efficiency for matrix multiplication at 500 MHz in 180 nm CMOS using a compressed Bent-Pyramid stochastic format.
-
Accurate and Robust Eye Contact Detection During Everyday Mobile Device Interactions
Extends unsupervised eye contact detection for mobile scenarios, reporting significant performance gains on two datasets and new attention metrics.