86 citations · 320 across the 23 of their papers we have counts for
23 papers
Constraints on Axion-like Particles from Observations of Mrk 421 using the Method
Lin-Qing Gao, Xiao-Jun Bi, Jun-Guang Guo +2
Axion-like particles (ALPs) may undergo mixing with photons in the presence of astrophysical magnetic fields, leading to alterations in the observed high energy -ray spectra. In…
Joint Participation Incentive and Network Pricing Design for Federated Learning
Ningning Ding, Lin Gao, Jianwei Huang
Federated learning protects users' data privacy through sharing users' local model parameters (instead of raw data) with a server. However, when massive users train a large machine…
SceneHGN: Hierarchical Graph Networks for 3D Indoor Scene Generation with Fine-Grained Geometry
Lin Gao, Jia-Mu Sun, Kaichun Mo +3
3D indoor scenes are widely used in computer graphics, with applications ranging from interior design to gaming to virtual and augmented reality. They also contain rich information…
NeRFFaceEditing: Disentangled Face Editing in Neural Radiance Fields
Kaiwen Jiang, Shu-Yu Chen, Feng-Lin Liu +2
Recent methods for synthesizing 3D-aware face images have achieved rapid development thanks to neural radiance fields, allowing for high quality and fast inference speed. However,…
StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning
Yi-Hua Huang, Yue He, Yu-Jie Yuan +2
3D scene stylization aims at generating stylized images of the scene from arbitrary novel views following a given set of style examples, while ensuring consistency when rendered fr…
NeRF-Editing: Geometry Editing of Neural Radiance Fields
Yu-Jie Yuan, Yang-Tian Sun, Yu-Kun Lai +3
Implicit neural rendering, especially Neural Radiance Field (NeRF), has shown great potential in novel view synthesis of a scene. However, current NeRF-based methods cannot enable…
Exploring Fermionic Multiplet Dark Matter through Precision Measurements at the CEPC
Lin-Qing Gao, Xiao-Jun Bi, Jin-Wei Wang +2
New physics could be explored through loop effects by the precision measurements at the Circular Electron Positron Collider due to its clean collision environment and high luminosi…
Taming Time-Varying Information Asymmetry in Fresh Status Acquisition
Zhiyuan Wang, Lin Gao, Jianwei Huang
Many online platforms are providing valuable real-time contents (e.g., traffic) by continuously acquiring the status of different Points of Interest (PoIs). In status acquisition,…
DSG-Net: Learning Disentangled Structure and Geometry for 3D Shape Generation
Jie Yang, Kaichun Mo, Yu-Kun Lai +2
D shape generation is a fundamental operation in computer graphics. While significant progress has been made, especially with recent deep generative models, it remains a challenge…
Deep Generation of Face Images from Sketches
Shu-Yu Chen, Wanchao Su, Lin Gao +2
Recent deep image-to-image translation techniques allow fast generation of face images from freehand sketches. However, existing solutions tend to overfit to sketches, thus requiri…
Fusion of labeled RFS densities with minimum information loss
Lin Gao, Giorgio Battistelli, Luigi Chisci
This paper addresses fusion of labeled random finite set (LRFS) densities according to the criterion of minimum information loss (MIL). The MIL criterion amounts to minimizing the…
Learning-based Real-time Detection of Intrinsic Reflectional Symmetry
Yi-Ling Qiao, Lin Gao, Shu-Zhi Liu +3
Reflectional symmetry is ubiquitous in nature. While extrinsic reflectional symmetry can be easily parametrized and detected, intrinsic symmetry is much harder due to the high solu…
LaplacianNet: Learning on 3D Meshes with Laplacian Encoding and Pooling
Yi-Ling Qiao, Lin Gao, Jie Yang +3
3D models are commonly used in computer vision and graphics. With the wider availability of mesh data, an efficient and intrinsic deep learning approach to processing 3D meshes is…
PRS-Net: Planar Reflective Symmetry Detection Net for 3D Models
Lin Gao, Ling-Xiao Zhang, Hsien-Yu Meng +3
In geometry processing, symmetry is a universal type of high-level structural information of 3D models and benefits many geometry processing tasks including shape segmentation, ali…
SDM-NET: Deep Generative Network for Structured Deformable Mesh
Lin Gao, Jie Yang, Tong Wu +4
We introduce SDM-NET, a deep generative neural network which produces structured deformable meshes. Specifically, the network is trained to generate a spatial arrangement of closed…
Realtime Simulation of Thin-Shell Deformable Materials using CNN-Based Mesh Embedding
Qingyang Tan, Zherong Pan, Lin Gao +1
We address the problem of accelerating thin-shell deformable object simulations by dimension reduction. We present a new algorithm to embed a high-dimensional configuration space o…
Mesh Variational Autoencoders with Edge Contraction Pooling
Yu-Jie Yuan, Yu-Kun Lai, Jie Yang +2
3D shape analysis is an important research topic in computer vision and graphics. While existing methods have generalized image-based deep learning to meshes using graph-based conv…
5G mmWave Cooperative Positioning and Mapping using Multi-Model PHD Filter and Map Fusion
Hyowon Kim, Karl Granström, Lin Gao +3
5G millimeter wave (mmWave) signals can enable accurate positioning in vehicular networks when the base station and vehicles are equipped with large antenna arrays. However, radio-…
VV-Net: Voxel VAE Net with Group Convolutions for Point Cloud Segmentation
Hsien-Yu Meng, Lin Gao, YuKun Lai +1
We present a novel algorithm for point cloud segmentation. Our approach transforms unstructured point clouds into regular voxel grids, and further uses a kernel-based interpolated…
Sparse Data Driven Mesh Deformation
Lin Gao, Yu-Kun Lai, Jie Yang +3
Example-based mesh deformation methods are powerful tools for realistic shape editing. However, existing techniques typically combine all the example deformation modes, which can l…
Variational Autoencoders for Deforming 3D Mesh Models
Qingyang Tan, Lin Gao, Yu-Kun Lai +1
3D geometric contents are becoming increasingly popular. In this paper, we study the problem of analyzing deforming 3D meshes using deep neural networks. Deforming 3D meshes are fl…
Mesh-based Autoencoders for Localized Deformation Component Analysis
Qingyang Tan, Lin Gao, Yu-Kun Lai +2
Spatially localized deformation components are very useful for shape analysis and synthesis in 3D geometry processing. Several methods have recently been developed, with an aim to…
Temporal Upsampling of Depth Maps Using a Hybrid Camera
Ming-Ze Yuan, Lin Gao, Hongbo Fu +1
In recent years, consumer-level depth cameras have been adopted for various applications. However, they often produce depth maps at only a moderately high frame rate (approximately…