no code implementations • 20 Dec 2023 • Yue-Jiang Dong, Yuan-Chen Guo, Ying-Tian Liu, Fang-Lue Zhang, Song-Hai Zhang
Self-supervised monocular depth estimation is of significant importance with applications spanning across autonomous driving and robotics.
no code implementations • 14 Dec 2023 • Ying-Tian Liu, Yuan-Chen Guo, Guan Luo, Heyi Sun, Wei Yin, Song-Hai Zhang
However, the generation quality and generalization ability of 3D diffusion models is hindered by the scarcity of high-quality and large-scale 3D datasets.
1 code implementation • CVPR 2023 • Ying-Tian Liu, Zhifei Zhang, Yuan-Chen Guo, Matthew Fisher, Zhaowen Wang, Song-Hai Zhang
Automatic generation of fonts can be an important aid to typeface design.
no code implementations • ICCV 2023 • Chia-Hao Chen, Ying-Tian Liu, Zhifei Zhang, Yuan-Chen Guo, Song-Hai Zhang
Existing vector font generation approaches either struggle to preserve high-frequency corner details of the glyph or produce vector shapes that have redundant segments, which hinders their applications in practical scenarios.
no code implementations • 10 Dec 2021 • Ying-Tian Liu, Yuan-Chen Guo, Song-Hai Zhang
Is the center position fully capable of representing a pixel?
no code implementations • 16 Jun 2021 • Ying-Tian Liu, Yuan-Chen Guo, Yi-Xiao Li, Chen Wang, Song-Hai Zhang
In this paper, we present a novel implicit glyph shape representation, which models glyphs as shape primitives enclosed by quadratic curves, and naturally enables generating glyph images at arbitrary high resolutions.