no code implementations • 7 Nov 2023 • Xingzhe He, Zhiwen Cao, Nicholas Kolkin, Lantao Yu, Kun Wan, Helge Rhodin, Ratheesh Kalarot
This strategy enables the model to preserve fine details of the desired subjects, such as text and logos.
no code implementations • ICCV 2021 • Alireza Zaeemzadeh, Shabnam Ghadar, Baldo Faieta, Zhe Lin, Nazanin Rahnavard, Mubarak Shah, Ratheesh Kalarot
For example, a user can ask for retrieving images similar to a query image, but with a different hair color, and no preference for absence/presence of eyeglasses in the results.
1 code implementation • 19 Oct 2019 • Ratheesh Kalarot, Tao Li, Fatih Porikli
To make the best use of the underlying structure of faces, the collective information through face datasets and the intermediate estimates during the upsampling process, here we introduce a fully convolutional multi-stage neural network for 4$\times$ super-resolution for face images.