no code implementations • 8 Dec 2023 • Xin Li, Peng Li, Zeyong Wei, Zhe Zhu, Mingqiang Wei, Junhui Hou, Liangliang Nan, Jing Qin, Haoran Xie, Fu Lee Wang
By performing cross-modal interaction, Cross-BERT can smoothly reconstruct the masked tokens during pretraining, leading to notable performance enhancements for downstream tasks.
1 code implementation • 27 Oct 2023 • Xiaokai Zhang, Na Zhu, Yiming He, Jia Zou, Qike Huang, Xiaoxiao Jin, Yanjun Guo, Chenyang Mao, Yang Li, Zhe Zhu, Dengfeng Yue, Fangzhen Zhu, Yifan Wang, Yiwen Huang, Runan Wang, Cheng Qin, Zhenbing Zeng, Shaorong Xie, Xiangfeng Luo, Tuo Leng
In this paper, we have constructed a consistent formal plane geometry system.
no code implementations • 8 Sep 2023 • Mengyao Cui, Zhe Zhu, Shao-Ping Lu, Yulu Yang
In this work, we attempt to stylize an input image using such coarsely matched text as guidance.
1 code implementation • ICCV 2023 • Zhe Zhu, Honghua Chen, Xing He, Weiming Wang, Jing Qin, Mingqiang Wei
In this paper, we propose a novel network, SVDFormer, to tackle two specific challenges in point cloud completion: understanding faithful global shapes from incomplete point clouds and generating high-accuracy local structures.
no code implementations • 28 Oct 2022 • Huajian Si, Zeyong Wei, Zhe Zhu, Honghua Chen, Dong Liang, Weiming Wang, Mingqiang Wei
Bilateral filter (BF) is a fast, lightweight and effective tool for image denoising and well extended to point cloud denoising.
4 code implementations • 5 Sep 2022 • Fei Hu, Honghua Chen, Xuequan Lu, Zhe Zhu, Jun Wang, Weiming Wang, Fu Lee Wang, Mingqiang Wei
We propose a novel stepwise point cloud completion network (SPCNet) for various 3D models with large missings.
no code implementations • 1 Aug 2022 • Zhe Zhu, Liangliang Nan, Haoran Xie, Honghua Chen, Mingqiang Wei, Jun Wang, Jing Qin
The first module transfers the intrinsic shape characteristics from single images to guide the geometry generation of the missing regions of point clouds, in which we propose IPAdaIN to embed the global features of both the image and the partial point cloud into completion.
Ranked #2 on Point Cloud Completion on ShapeNet-ViPC
1 code implementation • 9 Jun 2022 • Mingqiang Wei, Zeyong Wei, Haoran Zhou, Fei Hu, Huajian Si, Zhilei Chen, Zhe Zhu, Jingbo Qiu, Xuefeng Yan, Yanwen Guo, Jun Wang, Jing Qin
In this paper, we propose Adaptive Graph Convolution (AGConv) for wide applications of point cloud analysis.
no code implementations • 4 Dec 2021 • Diqiong Jiang, Yiwei Jin, FangLue Zhang, Zhe Zhu, Yun Zhang, Ruofeng Tong, Min Tang
However, the shape parameters of traditional 3DMMs satisfy the multivariate Gaussian distribution while the identity embeddings satisfy the hypersphere distribution, and this conflict makes it challenging for face reconstruction models to preserve the faithfulness and the shape consistency simultaneously.
1 code implementation • 3 Jul 2019 • Yinhao Ren, Zhe Zhu, Yingzhou Li, Joseph Lo
To use semantic masks as guidance whilst providing realistic synthesized results with fine details, we propose to use mask embedding mechanism to allow for a more efficient initial feature projection in the generator.
5 code implementations • 28 Feb 2018 • Tai-Ling Yuan, Zhe Zhu, Kun Xu, Cheng-Jun Li, Shi-Min Hu
[python3. 6] 运用tf实现自然场景文字检测, keras/pytorch实现ctpn+crnn+ctc实现不定长场景文字OCR识别
no code implementations • 29 Nov 2017 • Zhe Zhu, Ehab AlBadawy, Ashirbani Saha, Jun Zhang, Michael R. Harowicz, Maciej A. Mazurowski
Results: The best AUC performance for distinguishing molecular subtypes was 0. 65 (95% CI:[0. 57, 0. 71]) and was achieved by the off-the-shelf deep features approach.
no code implementations • 28 Nov 2017 • Zhe Zhu, Michael Harowicz, Jun Zhang, Ashirbani Saha, Lars J. Grimm, E. Shelley Hwang, Maciej A. Mazurowski
In the first approach, we adopted the transfer learning strategy, in which a network pre-trained on a large dataset of natural images is fine-tuned with our DCIS images.
no code implementations • 1 Jun 2016 • Zhe Zhu, Jiaming Lu, Minxuan Wang, Song-Hai Zhang, Ralph Martin, Hantao Liu, Shi-Min Hu
In this paper, we investigate 6 popular blending algorithms---feather blending, multi-band blending, modified Poisson blending, mean value coordinate blending, multi-spline blending and convolution pyramid blending.
no code implementations • CVPR 2016 • Zhe Zhu, Dun Liang, SongHai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu
We call this benchmark Tsinghua-Tencent 100K.