Mar 18, 2019 · We focus on extracting better features from eye images. Relatively large changes in gaze angles may result in relatively small changes in eye appearance.
May 26, 2019 · In this article, we propose to improve the accuracy of appearance-based gaze estimation by extracting higher resolution features from the eye images using deep ...
This work adopts dilated-convolutions to extract high-level features without reducing spatial resolution in gaze estimation and achieves state-of-the-art ...
The Pytorch Implementation of "Appearance-Based Gaze Estimation Using Dilated-Convolutions". (updated in 2021/04/28). We build benchmarks for gaze estimation in ...
Chen and Shi [9] showed that extracting features using dilated convolutions instead of regular convolutions improve gaze estimation accuracy. They argued that a ...
People also ask
What are the methods of gaze estimation?
What is the difference between convolution and dilated convolution?
Dilated convolutions achieve large receptive field without resorting to maxpooling layers. In simple terms, dilated convolution is a convolutional operation ...
We use dilated-convolutions to capture high-level features at high-resolution from eye images. We replace some regular convolutional layers and max-pooling ...
Gaze estimation has become an important field of image and information processing. Estimating gaze from full-face images using convolutional neural network (CNN) ...
In this paper, we propose a novel multimodal fusion gaze estimation model based on ConvNext and dilated convolution. In this model, the eye image and face image ...
Apr 30, 2024 · In this paper, we present a systematic review of the appearance-based gaze estimation methods using deep learning.