134 citations · 513 across the 41 of their papers we have counts for
42 papers
SketchMetaFace: A Learning-based Sketching Interface for High-fidelity 3D Character Face Modeling
Zhongjin Luo, Dong Du, Heming Zhu +3
Modeling 3D avatars benefits various application scenarios such as AR/VR, gaming, and filming. Character faces contribute significant diversity and vividity as a vital component of…
3DPortraitGAN: Learning One-Quarter Headshot 3D GANs from a Single-View Portrait Dataset with Diverse Body Poses
Yiqian Wu, Hao Xu, Xiangjun Tang +3
3D-aware face generators are typically trained on 2D real-life face image datasets that primarily consist of near-frontal face data, and as such, they are unable to construct one-q…
Sketch2Stress: Sketching with Structural Stress Awareness
Deng Yu, Chufeng Xiao, Manfred Lau +1
In the process of product design and digital fabrication, the structural analysis of a designed prototype is a fundamental and essential step. However, such a step is usually invis…
Sketch Beautification: Learning Part Beautification and Structure Refinement for Sketches of Man-made Objects
Deng Yu, Manfred Lau, Lin Gao +1
We present a novel freehand sketch beautification method, which takes as input a freely drawn sketch of a man-made object and automatically beautifies it both geometrically and str…
LPFF: A Portrait Dataset for Face Generators Across Large Poses
Yiqian Wu, Jing Zhang, Hongbo Fu +1
The creation of 2D realistic facial images and 3D face shapes using generative networks has been a hot topic in recent years. Existing face generators exhibit exceptional performan…
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,…
LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation
Zeyu Hu, Xuyang Bai, Runze Zhang +4
We propose LiDAL, a novel active learning method for 3D LiDAR semantic segmentation by exploiting inter-frame uncertainty among LiDAR frames. Our core idea is that a well-trained m…
MonoNeuralFusion: Online Monocular Neural 3D Reconstruction with Geometric Priors
Zi-Xin Zou, Shi-Sheng Huang, Yan-Pei Cao +3
High-fidelity 3D scene reconstruction from monocular videos continues to be challenging, especially for complete and fine-grained geometry reconstruction. The previous 3D reconstru…
DifferSketching: How Differently Do People Sketch 3D Objects?
Chufeng Xiao, Wanchao Su, Jing Liao +3
Multiple sketch datasets have been proposed to understand how people draw 3D objects. However, such datasets are often of small scale and cover a small set of objects or categories…
DeepPortraitDrawing: Generating Human Body Images from Freehand Sketches
Xian Wu, Chen Wang, Hongbo Fu +3
Researchers have explored various ways to generate realistic images from freehand sketches, e.g., for objects and human faces. However, how to generate realistic human body images…
NeuralHDHair: Automatic High-fidelity Hair Modeling from a Single Image Using Implicit Neural Representations
Keyu Wu, Yifan Ye, Lingchen Yang +3
Undoubtedly, high-fidelity 3D hair plays an indispensable role in digital humans. However, existing monocular hair modeling methods are either tricky to deploy in digital systems (…
PoseCoach: A Customizable Analysis and Visualization System for Video-based Running Coaching
Jingyuan Liu, Nazmus Saquib, Zhutian Chen +4
Videos are an accessible form of media for analyzing sports postures and providing feedback to athletes. Existing sport-specific systems embed bespoke human pose attributes and thu…
TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers
Xuyang Bai, Zeyu Hu, Xinge Zhu +4
LiDAR and camera are two important sensors for 3D object detection in autonomous driving. Despite the increasing popularity of sensor fusion in this field, the robustness against i…
NeuralReshaper: Single-image Human-body Retouching with Deep Neural Networks
Beijia Chen, Yuefan Shen, Hongbo Fu +3
In this paper, we present NeuralReshaper, a novel method for semantic reshaping of human bodies in single images using deep generative networks. To achieve globally coherent reshap…
DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN
Wanchao Su, Hui Ye, Shu-Yu Chen +2
The research topic of sketch-to-portrait generation has witnessed a boost of progress with deep learning techniques. The recently proposed StyleGAN architectures achieve state-of-t…
SketchHairSalon: Deep Sketch-based Hair Image Synthesis
Chufeng Xiao, Deng Yu, Xiaoguang Han +2
Recent deep generative models allow real-time generation of hair images from sketch inputs. Existing solutions often require a user-provided binary mask to specify a target hair sh…
Autocomplete Repetitive Stroking with Image Guidance
Yilan Chen, Kin Chung Kwan, Li-Yi Wei +1
Image-guided drawing can compensate for the lack of skills but often requires a significant number of repetitive strokes to create textures. Existing automatic stroke synthesis met…
GCN-Denoiser: Mesh Denoising with Graph Convolutional Networks
Yuefan Shen, Hongbo Fu, Zhongshuo Du +5
In this paper, we present GCN-Denoiser, a novel feature-preserving mesh denoising method based on graph convolutional networks (GCNs). Unlike previous learning-based mesh denoising…
SimpModeling: Sketching Implicit Field to Guide Mesh Modeling for 3D Animalmorphic Head Design
Zhongjin Luo, Jie Zhou, Heming Zhu +3
Head shapes play an important role in 3D character design. In this work, we propose SimpModeling, a novel sketch-based system for helping users, especially amateur users, easily mo…
WSDesc: Weakly Supervised 3D Local Descriptor Learning for Point Cloud Registration
Lei Li, Hongbo Fu, Maks Ovsjanikov
In this work, we present a novel method called WSDesc to learn 3D local descriptors in a weakly supervised manner for robust point cloud registration. Our work builds upon recent 3…
VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation
Zeyu Hu, Xuyang Bai, Jiaxiang Shang +6
In recent years, sparse voxel-based methods have become the state-of-the-arts for 3D semantic segmentation of indoor scenes, thanks to the powerful 3D CNNs. Nevertheless, being obl…
DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control
Shu-Yu Chen, Feng-Lin Liu, Yu-Kun Lai +4
Recent facial image synthesis methods have been mainly based on conditional generative models. Sketch-based conditions can effectively describe the geometry of faces, including the…
PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency
Xuyang Bai, Zixin Luo, Lei Zhou +5
Removing outlier correspondences is one of the critical steps for successful feature-based point cloud registration. Despite the increasing popularity of introducing deep learning…
Scale-aware Insertion of Virtual Objects in Monocular Videos
Songhai Zhang, Xiangli Li, Yingtian Liu +1
In this paper, we propose a scale-aware method for inserting virtual objects with proper sizes into monocular videos. To tackle the scale ambiguity problem of geometry recovery fro…