75 citations · 81 across the 4 of their papers we have counts for
4 papers
Data-free mixed-precision quantization using novel sensitivity metric
Donghyun Lee, Minkyoung Cho, Seungwon Lee +2
Post-training quantization is a representative technique for compressing neural networks, making them smaller and more efficient for deployment on edge devices. However, an inacces…
A Generalized and Robust Method Towards Practical Gaze Estimation on Smart Phone
Tianchu Guo, Yongchao Liu, Hui Zhang +5
Gaze estimation for ordinary smart phone, e.g. estimating where the user is looking at on the phone screen, can be applied in various applications. However, the widely used appeara…
Learning to Quantize Deep Networks by Optimizing Quantization Intervals with Task Loss
Sangil Jung, Changyong Son, Seohyung Lee +5
Reducing bit-widths of activations and weights of deep networks makes it efficient to compute and store them in memory, which is crucial in their deployments to resource-limited de…
Deep generative-contrastive networks for facial expression recognition
Youngsung Kim, ByungIn Yoo, Youngjun Kwak +2
As the expressive depth of an emotional face differs with individuals or expressions, recognizing an expression using a single facial image at a moment is difficult. A relative exp…