1 code implementation • 9 Oct 2024 • Hua Li, Zhouhui Lian
Using our method, for the first time, large-scale Chinese vector fonts of a quality comparable to those manually created by professional font designers can be automatically generated.
no code implementations • 29 Sep 2024 • Yiming Zhao, Dewen Guo, Zhouhui Lian, Yue Gao, Jianhong Han, Jie Feng, Guoping Wang, Bingfeng Zhou, Sheng Li
To bridge the gap between artists and non-specialists, we present a unified framework, Neural-Polyptych, to facilitate the creation of expansive, high-resolution paintings by seamlessly incorporating interactive hand-drawn sketches with fragments from original paintings.
1 code implementation • 27 Aug 2024 • Bojun Xiong, Si-Tong Wei, Xin-Yang Zheng, Yan-Pei Cao, Zhouhui Lian, Peng-Shuai Wang
Diffusion models have emerged as a popular method for 3D generation.
1 code implementation • 21 Aug 2024 • Guo Pu, Yiming Zhao, Zhouhui Lian
The key idea is to initially construct a preliminary mesh from the input panorama, and iteratively refine this mesh using a panoramic RGBD inpainter while collecting photo-realistic 3D-consistent pseudo novel views.
no code implementations • 1 Feb 2024 • Guo Pu, Shiyao Xu, Xixin Cao, Zhouhui Lian
How to automatically transfer the dynamic texture of a given video to the target still image is a challenging and ongoing problem.
no code implementations • CVPR 2024 • Yifang Men, Biwen Lei, Yuan YAO, Miaomiao Cui, Zhouhui Lian, Xuansong Xie
We present En3D, an enhanced generative scheme for sculpting high-quality 3D human avatars.
no code implementations • CVPR 2024 • Yifang Men, Hanxi Liu, Yuan YAO, Miaomiao Cui, Xuansong Xie, Zhouhui Lian
In this paper we make a connection between the two and tackle the challenging task of 3D portrait stylization - modeling high-fidelity 3D stylized avatars from captured 2D portrait images.
1 code implementation • CVPR 2024 • Jialei Cui, Jianwei Du, Wenzhuo LIU, Zhouhui Lian
Acquiring large-scale well-annotated datasets is essential for training robust scene text detectors yet the process is often resource-intensive and time-consuming.
1 code implementation • 18 Dec 2023 • Guo Pu, Peng-Shuai Wang, Zhouhui Lian
This paper proposes SinMPI, a novel method that uses an expanded multiplane image (MPI) as the 3D scene representation to significantly expand the perspective range of MPI and generate high-quality novel views from a large multiplane space.
1 code implementation • 16 Dec 2023 • Yitian Liu, Zhouhui Lian
Few-shot font generation, especially for Chinese calligraphy fonts, is a challenging and ongoing problem.
1 code implementation • 8 Dec 2023 • Yiming Zhao, Zhouhui Lian
Text-to-Image (T2I) generation methods based on diffusion model have garnered significant attention in the last few years.
1 code implementation • CVPR 2023 • Yuqing Wang, Yizhi Wang, Longhui Yu, Yuesheng Zhu, Zhouhui Lian
First, we adopt Transformers instead of RNNs to process sequential data and design a relaxation representation for vector outlines, markedly improving the model's capability and stability of synthesizing long and complex outlines.
no code implementations • CVPR 2023 • Zeqing Xia, Bojun Xiong, Zhouhui Lian
In this manner, most image generation methods can be easily extended to synthesize vector fonts.
no code implementations • 12 Oct 2022 • Yitian Liu, Zhouhui Lian
Automatic generation of high-quality Chinese fonts from a few online training samples is a challenging task, especially when the amount of samples is very small.
1 code implementation • 19 Sep 2022 • Chufeng Xiao, Wanchao Su, Jing Liao, Zhouhui Lian, Yi-Zhe Song, Hongbo Fu
We invited 70 novice users and 38 expert users to sketch 136 3D objects, which were presented as 362 images rendered from multiple views.
3 code implementations • 6 Jul 2022 • Yifang Men, Yuan YAO, Miaomiao Cui, Zhouhui Lian, Xuansong Xie
This paper introduces DCT-Net, a novel image translation architecture for few-shot portrait stylization.
1 code implementation • CVPR 2022 • Yizhi Wang, Guo Pu, Wenhan Luo, Yexin Wang, Pengfei Xiong, Hongwen Kang, Zhouhui Lian
To train and evaluate our approach, we construct a dataset named as TextLogo3K, consisting of about 3, 500 text logo images and their pixel-level annotations.
no code implementations • CVPR 2022 • Yifang Men, Yuan YAO, Miaomiao Cui, Zhouhui Lian, Xuansong Xie, Xian-Sheng Hua
Experimental results demonstrate the superiority of the proposed method over the state of the art and validate its effectiveness in the brand-new task of general cartoon image synthesis.
2 code implementations • 13 Oct 2021 • Yizhi Wang, Zhouhui Lian
Automatic font generation based on deep learning has aroused a lot of interest in the last decade.
1 code implementation • NeurIPS 2021 • Tao Sheng, Jie Chen, Zhouhui Lian
For the task of end-to-end scene text recognition, our method outperforms Mask TextSpotter v3 by 1. 1% on Total-Text.
no code implementations • 13 Jul 2021 • Tao Sheng, Zhouhui Lian
Arbitrary-shaped text detection has recently attracted increasing interests and witnessed rapid development with the popularity of deep learning algorithms.
1 code implementation • Computer Graphics Forum 2021 • Shusen Tang, Zhouhui Lian
Then, our entire model is trained in an end-to-end manner and the decoder adaptively receives the style information from the style encoder and the content information from the content encoder to synthesize the target output.
no code implementations • CVPR 2021 • Yue Gao, Fangyun Wei, Jianmin Bao, Shuyang Gu, Dong Chen, Fang Wen, Zhouhui Lian
However, we observe that the generator tends to find a tricky way to hide information from the original image to satisfy the constraint of cycle consistency, making it impossible to maintain the rich details (e. g., wrinkles and moles) of non-editing areas.
no code implementations • 16 Sep 2020 • Yizhi Wang, Zhouhui Lian
Scene text recognition (STR) has been extensively studied in last few years.
2 code implementations • 16 May 2020 • Yizhi Wang, Yue Gao, Zhouhui Lian
To the best of our knowledge, our model is the first one in the literature which is capable of generating glyph images in new font styles, instead of retrieving existing fonts, according to given values of specified font attributes.
2 code implementations • CVPR 2020 • Yifang Men, Yiming Mao, Yuning Jiang, Wei-Ying Ma, Zhouhui Lian
This paper introduces the Attribute-Decomposed GAN, a novel generative model for controllable person image synthesis, which can produce realistic person images with desired human attributes (e. g., pose, head, upper clothes and pants) provided in various source inputs.
Ranked #6 on Pose Transfer on Deep-Fashion
no code implementations • 1 Mar 2020 • David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, A Bronstein, M Bronstein, S Bu, Umberto Castellani, S Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, L Lai, Bo Li, C. Li, Haisheng Li, Roee Litman, X. Liu, Z Liu, Yijuan Lu, L. Sun, G Tam, Atsushi Tatsuma, J. Ye
In addition, further participants have also taken part, and we provide extra analysis of the retrieval results.
1 code implementation • Computer Graphics Forum 2019 • Shusen Tang, Zeqing Xia, Zhouhui Lian, Yingmin Tang, Jianguo Xiao
Despite the recent impressive development of deep neural networks, using deep learning based methods to generate large-scale Chinese fonts is still a rather challenging task due to the huge number of intricate Chinese glyphs, e. g., the official standard Chinese charset GB18030-2000 consists of 27, 533 Chinese characters.
no code implementations • 6 Nov 2019 • Xiao Sun, Zhouhui Lian, Jianguo Xiao
Point cloud analysis has drawn broader attentions due to its increasing demands in various fields.
3 code implementations • 11 Oct 2019 • Yue Gao, Yuan Guo, Zhouhui Lian, Yingmin Tang, Jianguo Xiao
Extensive experiments on both English and Chinese artistic glyph image datasets demonstrate the superiority of our model in generating high-quality stylized glyph images against other state-of-the-art methods.
Ranked #1 on Glyph Image Generation on English Glyph
1 code implementation • 12 Jul 2019 • Yizhi Wang, Zhouhui Lian, Yingmin Tang, Jianguo Xiao
In this paper, we propose a novel methodology for boosting scene character recognition by learning canonical forms of glyphs, based on the fact that characters appearing in scene images are all derived from their corresponding canonical forms.
no code implementations • CVPR 2018 • Yifang Men, Zhouhui Lian, Yingmin Tang, Jianguo Xiao
In this paper, we present a general-purpose solution to interactive texture transfer problems that better preserves both local structure and visual richness.
no code implementations • CVPR 2017 • Juncheng Liu, Zhouhui Lian, Yi Wang, Jianguo Xiao
This validates the superiority of our IKNDA against the state of the art in novelty detection for large-scale data.
1 code implementation • CVPR 2017 • Shuai Yang, Jiaying Liu, Zhouhui Lian, Zongming Guo
It allows our algorithm to produce artistic typography that fits for both local texture patterns and the global spatial distribution in the example.