Search Results for author: Lin Gao

Found 34 papers, 6 papers with code

StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning

no code implementations24 May 2022 Yi-Hua Huang, Yue He, Yu-Jie Yuan, Yu-Kun Lai, Lin Gao

We first pre-train a standard NeRF of the 3D scene to be stylized and replace its color prediction module with a style network to obtain a stylized NeRF.

Image Stylization

NeRF-Editing: Geometry Editing of Neural Radiance Fields

no code implementations10 May 2022 Yu-Jie Yuan, Yang-tian Sun, Yu-Kun Lai, Yuewen Ma, Rongfei Jia, Lin Gao

In this paper, we propose a method that allows users to perform controllable shape deformation on the implicit representation of the scene, and synthesizes the novel view images of the edited scene without re-training the network.

Neural Rendering Novel View Synthesis

DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN

no code implementations5 Mar 2022 Wanchao Su, Hui Ye, Shu-Yu Chen, Lin Gao, Hongbo Fu

The research topic of sketch-to-portrait generation has witnessed a boost of progress with deep learning techniques.

Image Generation

Socially-Optimal Mechanism Design for Incentivized Online Learning

no code implementations29 Dec 2021 Zhiyuan Wang, Lin Gao, Jianwei Huang

Multi-arm bandit (MAB) is a classic online learning framework that studies the sequential decision-making in an uncertain environment.

Decision Making Edge-computing +2

High-Fidelity Point Cloud Completion with Low-Resolution Recovery and Noise-Aware Upsampling

no code implementations21 Dec 2021 Ren-Wu Li, Bo wang, Chun-Peng Li, Ling-Xiao Zhang, Lin Gao

Instead of decoding a whole shape, we propose to decode and refine a low-resolution (low-res) point cloud first, and then performs a patch-wise noise-aware upsampling rather than interpolating the whole sparse point cloud at once, which tends to lose details.

Point Cloud Completion

OctField: Hierarchical Implicit Functions for 3D Modeling

no code implementations NeurIPS 2021 Jia-Heng Tang, Weikai Chen, Jie Yang, Bo wang, Songrun Liu, Bo Yang, Lin Gao

We achieve this goal by introducing a hierarchical octree structure to adaptively subdivide the 3D space according to the surface occupancy and the richness of part geometry.

Multi-sensor joint target detection, tracking and classification via Bernoulli filter

no code implementations23 Sep 2021 Gaiyou Li, Ping Wei, Giorgio Battistelli, Luigi Chisci, Lin Gao

This paper focuses on \textit{joint detection, tracking and classification} (JDTC) of a target via multi-sensor fusion.

Robust Pose Transfer with Dynamic Details using Neural Video Rendering

no code implementations27 Jun 2021 Yang-tian Sun, Hao-Zhi Huang, Xuan Wang, Yu-Kun Lai, Wei Liu, Lin Gao

Moreover, we introduce a concise temporal loss in the training stage to suppress the detail flickering that is made more visible due to high-quality dynamic details generated by our method.

Neural Rendering Pose Transfer +1

Autoregressive Stylized Motion Synthesis With Generative Flow

no code implementations CVPR 2021 Yu-Hui Wen, Zhipeng Yang, Hongbo Fu, Lin Gao, Yanan sun, Yong-Jin Liu

Motion style transfer is an important problem in many computer graphics and computer vision applications, including human animation, games, and robotics.

motion style transfer Style Transfer

Deep Deformation Detail Synthesis for Thin Shell Models

no code implementations23 Feb 2021 Lan Chen, Lin Gao, Jie Yang, Shibiao Xu, Juntao Ye, Xiaopeng Zhang, Yu-Kun Lai

Moreover, as such methods only add details, they require coarse meshes to be close to fine meshes, which can be either impossible, or require unrealistic constraints when generating fine meshes.

Frame

Single Image 3D Shape Retrieval via Cross-Modal Instance and Category Contrastive Learning

no code implementations ICCV 2021 Ming-Xian Lin, Jie Yang, He Wang, Yu-Kun Lai, Rongfei Jia, Binqiang Zhao, Lin Gao

Inspired by the great success in recent contrastive learning works on self-supervised representation learning, we propose a novel IBSR pipeline leveraging contrastive learning.

3D Shape Retrieval Contrastive Learning +3

Multiscale Mesh Deformation Component Analysis with Attention-based Autoencoders

no code implementations4 Dec 2020 Jie Yang, Lin Gao, Qingyang Tan, Yihua Huang, Shihong Xia, Yu-Kun Lai

The attention mechanism is designed to learn to softly weight multi-scale deformation components in active deformation regions, and the stacked attention-based autoencoder is learned to represent the deformation components at different scales.

TM-NET: Deep Generative Networks for Textured Meshes

no code implementations13 Oct 2020 Lin Gao, Tong Wu, Yu-Jie Yuan, Ming-Xian Lin, Yu-Kun Lai, Hao Zhang

We introduce a conditional autoregressive model for texture generation, which can be conditioned on both part geometry and textures already generated for other parts to achieve texture compatibility.

Graphics

RISA-Net: Rotation-Invariant Structure-Aware Network for Fine-Grained 3D Shape Retrieval

1 code implementation2 Oct 2020 Rao Fu, Jie Yang, Jiawei Sun, Fang-Lue Zhang, Yu-Kun Lai, Lin Gao

Fine-grained 3D shape retrieval aims to retrieve 3D shapes similar to a query shape in a repository with models belonging to the same class, which requires shape descriptors to be capable of representing detailed geometric information to discriminate shapes with globally similar structures.

3D Object Retrieval 3D Shape Retrieval

DSG-Net: Learning Disentangled Structure and Geometry for 3D Shape Generation

1 code implementation12 Aug 2020 Jie Yang, Kaichun Mo, Yu-Kun Lai, Leonidas J. Guibas, Lin Gao

While significant progress has been made, especially with recent deep generative models, it remains a challenge to synthesize high-quality shapes with rich geometric details and complex structure, in a controllable manner.

3D Shape Generation

Deep Generation of Face Images from Sketches

1 code implementation1 Jun 2020 Shu-Yu Chen, Wanchao Su, Lin Gao, Shihong Xia, Hongbo Fu

Our method essentially uses input sketches as soft constraints and is thus able to produce high-quality face images even from rough and/or incomplete sketches.

Image-to-Image Translation Translation

Deep Line Art Video Colorization with a Few References

no code implementations24 Mar 2020 Min Shi, Jia-Qi Zhang, Shu-Yu Chen, Lin Gao, Yu-Kun Lai, Fang-Lue Zhang

The color transform network takes the target line art images as well as the line art and color images of one or more reference images as input, and generates corresponding target color images.

Colorization

A Node Embedding Framework for Integration of Similarity-based Drug Combination Prediction

no code implementations25 Feb 2020 Liang Yu, Mingfei Xia, Lin Gao

Results: In this paper, we proposed a Network Embedding framework in Multiplex Networks (NEMN) to predict synthetic drug combinations.

Network Embedding

A Survey on Deep Geometry Learning: From a Representation Perspective

no code implementations19 Feb 2020 Yun-Peng Xiao, Yu-Kun Lai, Fang-Lue Zhang, Chunpeng Li, Lin Gao

However, the performance for different applications largely depends on the representation used, and there is no unique representation that works well for all applications.

Graphics

Learning-based Real-time Detection of Intrinsic Reflectional Symmetry

no code implementations1 Nov 2019 Yi-Ling Qiao, Lin Gao, Shu-Zhi Liu, Ligang Liu, Yu-Kun Lai, Xilin Chen

In this paper, we propose \YL{a} learning-based approach to intrinsic reflectional symmetry detection.

Symmetry Detection

PRS-Net: Planar Reflective Symmetry Detection Net for 3D Models

1 code implementation15 Oct 2019 Lin Gao, Ling-Xiao Zhang, Hsien-Yu Meng, Yi-Hui Ren, Yu-Kun Lai, Leif Kobbelt

In this paper, we present a novel learning framework to automatically discover global planar reflective symmetry of a 3D shape.

Symmetry Detection

Realtime Simulation of Thin-Shell Deformable Materials using CNN-Based Mesh Embedding

no code implementations26 Sep 2019 Qingyang Tan, Zherong Pan, Lin Gao, Dinesh Manocha

We present a new algorithm to embed a high-dimensional configuration space of deformable objects in a low-dimensional feature space, where the configurations of objects and feature points have approximate one-to-one mapping.

Dimensionality Reduction

5G mmWave Cooperative Positioning and Mapping using Multi-Model PHD Filter and Map Fusion

1 code implementation26 Aug 2019 Hyowon Kim, Karl Granström, Lin Gao, Giorgio Battistelli, Sunwoo Kim, Henk Wymeersch

5G millimeter wave (mmWave) signals can enable accurate positioning in vehicular networks when the base station (BS) and vehicles are equipped with large antenna arrays.

SDM-NET: Deep Generative Network for Structured Deformable Mesh

no code implementations13 Aug 2019 Lin Gao, Jie Yang, Tong Wu, Yu-Jie Yuan, Hongbo Fu, Yu-Kun Lai, Hao Zhang

At the structural level, we train a Structured Parts VAE (SP-VAE), which jointly learns the part structure of a shape collection and the part geometries, ensuring a coherence between global shape structure and surface details.

Mesh Variational Autoencoders with Edge Contraction Pooling

1 code implementation7 Aug 2019 Yu-Jie Yuan, Yu-Kun Lai, Jie Yang, Hongbo Fu, Lin Gao

3D shape analysis is an important research topic in computer vision and graphics.

VV-Net: Voxel VAE Net with Group Convolutions for Point Cloud Segmentation

no code implementations ICCV 2019 Hsien-Yu Meng, Lin Gao, Yu-Kun Lai, Dinesh Manocha

Our approach results in a good volumetric representation that effectively tackles noisy point cloud datasets and is more robust for learning.

Graphics

Learning Bidirectional LSTM Networks for Synthesizing 3D Mesh Animation Sequences

no code implementations4 Oct 2018 Yi-Ling Qiao, Lin Gao, Yu-Kun Lai, Shihong Xia

In this paper, we present a novel method for learning to synthesize 3D mesh animation sequences with long short-term memory (LSTM) blocks and mesh-based convolutional neural networks (CNNs).

Graphics

Mesh-based Autoencoders for Localized Deformation Component Analysis

no code implementations13 Sep 2017 Qingyang Tan, Lin Gao, Yu-Kun Lai, Jie Yang, Shihong Xia

Spatially localized deformation components are very useful for shape analysis and synthesis in 3D geometry processing.

Graphics

Sparse Data Driven Mesh Deformation

no code implementations5 Sep 2017 Lin Gao, Yu-Kun Lai, Jie Yang, Ling-Xiao Zhang, Leif Kobbelt, Shihong Xia

This along with a suitably chosen deformation basis including spatially localized deformation modes leads to significant advantages, including more meaningful, reliable, and efficient deformations because fewer and localized deformation modes are applied.

Graphics

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