Search Results for author: Huikai Wu

Found 9 papers, 7 papers with code

AI-enabled Automatic Multimodal Fusion of Cone-Beam CT and Intraoral Scans for Intelligent 3D Tooth-Bone Reconstruction and Clinical Applications

no code implementations11 Mar 2022 Jin Hao, Jiaxiang Liu, Jin Li, Wei Pan, Ruizhe Chen, Huimin Xiong, Kaiwei Sun, Hangzheng Lin, Wanlu Liu, Wanghui Ding, Jianfei Yang, Haoji Hu, Yueling Zhang, Yang Feng, Zeyu Zhao, Huikai Wu, Youyi Zheng, Bing Fang, Zuozhu Liu, Zhihe Zhao

Here, we present a Deep Dental Multimodal Analysis (DDMA) framework consisting of a CBCT segmentation model, an intraoral scan (IOS) segmentation model (the most accurate digital dental model), and a fusion model to generate 3D fused crown-root-bone structures with high fidelity and accurate occlusal and dentition information.

Segmentation

Point Cloud Super Resolution with Adversarial Residual Graph Networks

1 code implementation arXiv:1908.02111 2019 Huikai Wu, Junge Zhang, Kaiqi Huang

The key idea of the proposed network is to exploit the local similarity of point cloud and the analogy between LR input and HR output.

Graphics Image and Video Processing

SparseMask: Differentiable Connectivity Learning for Dense Image Prediction

1 code implementation ICCV 2019 Huikai Wu, Junge Zhang, Kaiqi Huang

In this paper, we aim at automatically searching an efficient network architecture for dense image prediction.

FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation

12 code implementations28 Mar 2019 Huikai Wu, Junge Zhang, Kaiqi Huang, Kongming Liang, Yizhou Yu

Modern approaches for semantic segmentation usually employ dilated convolutions in the backbone to extract high-resolution feature maps, which brings heavy computation complexity and memory footprint.

Semantic Segmentation

Fast End-to-End Trainable Guided Filter

1 code implementation CVPR 2018 Huikai Wu, Shuai Zheng, Junge Zhang, Kaiqi Huang

To address the problem, we present a novel building block for FCNs, namely guided filtering layer, which is designed for efficiently generating a high-resolution output given the corresponding low-resolution one and a high-resolution guidance map.

MSC: A Dataset for Macro-Management in StarCraft II

2 code implementations9 Oct 2017 Huikai Wu, Yanqi Zong, Junge Zhang, Kaiqi Huang

We also split MSC into training, validation and test set for the convenience of evaluation and comparison.

Management Starcraft +1

GP-GAN: Towards Realistic High-Resolution Image Blending

2 code implementations21 Mar 2017 Huikai Wu, Shuai Zheng, Junge Zhang, Kaiqi Huang

Concretely, we propose Gaussian-Poisson Equation to formulate the high-resolution image blending problem, which is a joint optimization constrained by the gradient and color information.

Conditional Image Generation Generative Adversarial Network +1

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