Search Results for author: Youyi Zheng

Found 20 papers, 9 papers with code

AniDress: Animatable Loose-Dressed Avatar from Sparse Views Using Garment Rigging Model

no code implementations27 Jan 2024 Beijia Chen, Yuefan Shen, Qing Shuai, Xiaowei Zhou, Kun Zhou, Youyi Zheng

In this paper, we introduce AniDress, a novel method for generating animatable human avatars in loose clothes using very sparse multi-view videos (4-8 in our setting).

VDN-NeRF: Resolving Shape-Radiance Ambiguity via View-Dependence Normalization

1 code implementation CVPR 2023 Bingfan Zhu, Yanchao Yang, Xulong Wang, Youyi Zheng, Leonidas Guibas

We propose VDN-NeRF, a method to train neural radiance fields (NeRFs) for better geometry under non-Lambertian surface and dynamic lighting conditions that cause significant variation in the radiance of a point when viewed from different angles.

OrthoGAN:High-Precision Image Generation for Teeth Orthodontic Visualization

no code implementations29 Dec 2022 Feihong Shen, Jingjing Liu, Haizhen Li, Bing Fang, Chenglong Ma, Jin Hao, Yang Feng, Youyi Zheng

We design a multi-modal encoder-decoder based generative model to synthesize identity-preserving frontal facial images with aligned teeth.

Decoder Image Generation

NeuralHDHair: Automatic High-fidelity Hair Modeling from a Single Image Using Implicit Neural Representations

no code implementations CVPR 2022 Keyu Wu, Yifan Ye, Lingchen Yang, Hongbo Fu, Kun Zhou, Youyi Zheng

To improve the efficiency of a traditional hair growth algorithm, we adopt a local neural implicit function to grow strands based on the estimated 3D hair geometric features.

NeuralReshaper: Single-image Human-body Retouching with Deep Neural Networks

no code implementations20 Mar 2022 Beijia Chen, Yuefan Shen, Hongbo Fu, Xiang Chen, Kun Zhou, Youyi Zheng

In this paper, we present NeuralReshaper, a novel method for semantic reshaping of human bodies in single images using deep generative networks.

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

ADeLA: Automatic Dense Labeling With Attention for Viewpoint Shift in Semantic Segmentation

no code implementations CVPR 2022 Hanxiang Ren, Yanchao Yang, He Wang, Bokui Shen, Qingnan Fan, Youyi Zheng, C. Karen Liu, Leonidas J. Guibas

We describe a method to deal with performance drop in semantic segmentation caused by viewpoint changes within multi-camera systems, where temporally paired images are readily available, but the annotations may only be abundant for a few typical views.

Hallucination Semantic Segmentation +1

Domain Adaptation on Point Clouds via Geometry-Aware Implicits

1 code implementation CVPR 2022 Yuefan Shen, Yanchao Yang, Mi Yan, He Wang, Youyi Zheng, Leonidas Guibas

Here we propose a simple yet effective method for unsupervised domain adaptation on point clouds by employing a self-supervised task of learning geometry-aware implicits, which plays two critical roles in one shot.

Autonomous Driving Unsupervised Domain Adaptation

SketchHairSalon: Deep Sketch-based Hair Image Synthesis

no code implementations16 Sep 2021 Chufeng Xiao, Deng Yu, Xiaoguang Han, Youyi Zheng, Hongbo Fu

At the second stage, another network is trained to synthesize the structure and appearance of hair images from the input sketch and the generated matte.

Image Generation

ADeLA: Automatic Dense Labeling with Attention for Viewpoint Adaptation in Semantic Segmentation

1 code implementation29 Jul 2021 Yanchao Yang, Hanxiang Ren, He Wang, Bokui Shen, Qingnan Fan, Youyi Zheng, C. Karen Liu, Leonidas Guibas

Furthermore, to resolve ambiguities in converting the semantic images to semantic labels, we treat the view transformation network as a functional representation of an unknown mapping implied by the color images and propose functional label hallucination to generate pseudo-labels in the target domain.

Hallucination Inductive Bias +2

DCL: Differential Contrastive Learning for Geometry-Aware Depth Synthesis

2 code implementations27 Jul 2021 Yuefan Shen, Yanchao Yang, Youyi Zheng, C. Karen Liu, Leonidas Guibas

We describe a method for unpaired realistic depth synthesis that learns diverse variations from the real-world depth scans and ensures geometric consistency between the synthetic and synthesized depth.

Contrastive Learning Image Generation

AutoSweep: Recovering 3D Editable Objectsfrom a Single Photograph

1 code implementation27 May 2020 Xin Chen, Yuwei Li, Xi Luo, Tianjia Shao, Jingyi Yu, Kun Zhou, Youyi Zheng

We base our work on the assumption that most human-made objects are constituted by parts and these parts can be well represented by generalized primitives.

3D Reconstruction Instance Segmentation +1

SketchGNN: Semantic Sketch Segmentation with Graph Neural Networks

1 code implementation2 Mar 2020 Lumin Yang, Jiajie Zhuang, Hongbo Fu, Xiangzhi Wei, Kun Zhou, Youyi Zheng

We introduce SketchGNN, a convolutional graph neural network for semantic segmentation and labeling of freehand vector sketches.

Graph Neural Network Segmentation +1

SketchDesc: Learning Local Sketch Descriptors for Multi-view Correspondence

no code implementations16 Jan 2020 Deng Yu, Lei LI, Youyi Zheng, Manfred Lau, Yi-Zhe Song, Chiew-Lan Tai, Hongbo Fu

In this paper, we study the problem of multi-view sketch correspondence, where we take as input multiple freehand sketches with different views of the same object and predict as output the semantic correspondence among the sketches.

Semantic correspondence

Latent-Space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds

1 code implementation13 Dec 2019 Vage Egiazarian, Savva Ignatyev, Alexey Artemov, Oleg Voynov, Andrey Kravchenko, Youyi Zheng, Luiz Velho, Evgeny Burnaev

Constructing high-quality generative models for 3D shapes is a fundamental task in computer vision with diverse applications in geometry processing, engineering, and design.

Generating 3D Point Clouds Representation Learning

DeepSketchHair: Deep Sketch-based 3D Hair Modeling

1 code implementation20 Aug 2019 Yuefan Shen, Changgeng Zhang, Hongbo Fu, Kun Zhou, Youyi Zheng

The key enablers of our system are two carefully designed neural networks, namely, S2ONet, which converts an input sketch to a dense 2D hair orientation field; and O2VNet, which maps the 2D orientation field to a 3D vector field.

Graphics

Sketch-R2CNN: An Attentive Network for Vector Sketch Recognition

no code implementations20 Nov 2018 Lei Li, Changqing Zou, Youyi Zheng, Qingkun Su, Hongbo Fu, Chiew-Lan Tai

To bridge the gap between these two spaces in neural networks, we propose a neural line rasterization module to convert the vector sketch along with the attention estimated by RNN into a bitmap image, which is subsequently consumed by CNN.

Sketch Recognition

Hair-GANs: Recovering 3D Hair Structure from a Single Image

1 code implementation15 Nov 2018 Meng Zhang, Youyi Zheng

We introduce Hair-GANs, an architecture of generative adversarial networks, to recover the 3D hair structure from a single image.

Graphics

Recovering 3D Planar Arrangements from Videos

no code implementations25 Jan 2017 Shuai Du, Youyi Zheng

Acquiring 3D geometry of real world objects has various applications in 3D digitization, such as navigation and content generation in virtual environments.

3D Reconstruction

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