Marcello Restelli - IEEE Xplore Author Profile

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Author details

Marcello Restelli

Also published under: M. Restelli

Publications

31

Citations

272

Publications by Year

20042024

Co-Authors:

Emilia AmbrosiniLuca BascettaMario BerahaAndrea BonariniPaolo Bonetti

Show All Co-Authors (62)

Marcello Restelli

Also published under: M. Restelli

Affiliation

Diparimento di Elettronica

Informazione e Bioingegneria Politecnico di Milano

Milan, Italy

Publication Topics

Markov Decision Process,
Supervised Learning,
Curse Of Dimensionality,
Deep Reinforcement Learning,
Density Estimation,
Optimal Policy,
Proximal Policy Optimization,
Reinforcement Learning Algorithm,
Transition Model,
Actual Environment,
Aged Material,
Air Quality

Biography

Marcello Restelli received the Dr.Eng. degree in computer science engineering and the Ph.D. degree in information engineering from the Politecnico di Milano, Milano, Italy, in 2000 and 2004, respectively.,Since 2008, he has been an Assistant Professor with the Politecnico di Milano, where he has held various courses in the areas of machine learning and robotics. His current research interests include machine learning, reinforcement learning, multiarmed bandit, and robot learning.(Based on document published on 26 October 2015).

Publications

31

Citations

272

Publications by Year

20042024

Co-Authors:

Emilia Ambrosini
Luca Bascetta
Mario Beraha
Andrea Bonarini
Paolo Bonetti

Show All Co-Authors (62)

Author's Published Works

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Showing 1-25 of 50 results

Journals (34)

Conferences (14)

Early Access Articles (2)

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University of Chinese Academy of Sciences, Beijing, China(29)
Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China(26)
University of Chinese Academy of Sciences(7)
School of Creative Media, City University of Hong Kong, Hong Kong(6)
Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences(6)
IEEE Transactions on Visualization and Computer Graphics(20)
IEEE Transactions on Pattern Analysis and Machine Intelligence(12)
2021 IEEE/CVF International Conference on Computer Vision (ICCV)(2)
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(2)
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(2)
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VD-NeRF: Visibility-aware Decoupled Neural Radiance Fields for View-Consistent Editing and High-Frequency Relighting

Tong Wu;Jia-Mu Sun;Yu-Kun Lai;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2025 | Early Access Article |

Neural Radiance Fields (NeRFs) have shown promising results in novel view synthesis. While achieving state-of-the-art rendering results, NeRF usually encodes all properties related to geometry and appearance of the scene together into several MLP (Multi-Layer Perceptron) networks, which hinders downstream manipulation of geometry, appearance and illumination. Recently researchers made attempts to ...Show More

VD-NeRF: Visibility-aware Decoupled Neural Radiance Fields for View-Consistent Editing and High-Frequency Relighting

Tong Wu;Jia-Mu Sun;Yu-Kun Lai;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2025 | Early Access Article |

Towards High-Quality and Disentangled Face Editing in a 3D GAN

Kaiwen Jiang;Shu-Yu Chen;Feng-Lin Liu;Hongbo Fu;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2025 | Volume: 47, Issue: 4 | Journal Article |

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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, existing solutions for editing facial geometry and appearance independently usually require retraining and are not optimized for the recent work of generation, thus tending to lag behind the generation process. To addres...Show More

Towards High-Quality and Disentangled Face Editing in a 3D GAN

Kaiwen Jiang;Shu-Yu Chen;Feng-Lin Liu;Hongbo Fu;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2025 | Volume: 47, Issue: 4 | Journal Article |

MuNeRF: Robust Makeup Transfer in Neural Radiance Fields

Yu-Jie Yuan;Xinyang Han;Yue He;Fang-Lue Zhang;Lin Gao

IEEE Transactions on Visualization and Computer Graphics

Year: 2025 | Volume: 31, Issue: 3 | Journal Article |

Cited by: Papers (2)

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There has been a high demand for facial makeup transfer tools in fashion e-commerce and virtual avatar generation. Most of the existing makeup transfer methods are based on the generative adversarial networks. Despite their success in makeup transfer for a single image, they struggle to maintain the consistency of makeup under different poses and expressions of the same person. In this article, we...Show More

MuNeRF: Robust Makeup Transfer in Neural Radiance Fields

Yu-Jie Yuan;Xinyang Han;Yue He;Fang-Lue Zhang;Lin Gao

IEEE Transactions on Visualization and Computer Graphics

Year: 2025 | Volume: 31, Issue: 3 | Journal Article |

Real-Time 3D-Aware Portrait Video Relighting

Ziqi Cai;Kaiwen Jiang;Shu-Yu Chen;Yu-Kun Lai;Hongbo Fu;Boxin Shi;Lin Gao

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2024 | Conference Paper |

Cited by: Papers (2)

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Synthesizing realistic videos of talking faces under custom lighting conditions and viewing angles benefits various downstream applications like video conferencing. However, most existing relighting methods are either time-consuming or unable to adjust the viewpoints. In this paper, we present the first real-time 3D-aware method for relighting in-the-wild videos of talking faces based on Neural Ra...Show More

Real-Time 3D-Aware Portrait Video Relighting

Ziqi Cai;Kaiwen Jiang;Shu-Yu Chen;Yu-Kun Lai;Hongbo Fu;Boxin Shi;Lin Gao

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2024 | Conference Paper |

Unsigned Orthogonal Distance Fields: An Accurate Neural Implicit Representation for Diverse 3D Shapes

Yujie Lu;Long Want;Nayu Ding;Yulong Wang;Shuhan Shen;Shen Cai;Lin Gao

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2024 | Conference Paper |

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Neural implicit representation of geometric shapes has witnessed considerable advancements in recent years. However, common distance field based implicit represen-tations, specifically signed distance field (SDF) for water-tight shapes or unsigned distance field (UDF) for arbitrary shapes, routinely suffer from degradation of reconstruction accuracy when converting to explicit surface points and m...Show More

Unsigned Orthogonal Distance Fields: An Accurate Neural Implicit Representation for Diverse 3D Shapes

Yujie Lu;Long Want;Nayu Ding;Yulong Wang;Shuhan Shen;Shen Cai;Lin Gao

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2024 | Conference Paper |

HSDF: Hybrid Sign and Distance Field for Neural Representation of Surfaces with Arbitrary Topologies

Li Wang;Yu-Tao Liu;Jie Yang;Weikai Chen;Xiaoxu Meng;Bo Yang;Jintao Li;Lin Gao

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Early Access Article |

Neural implicit function based on signed distance field (SDF) has achieved impressive progress in reconstructing 3D models with high fidelity. However, such approaches can only represent closed surfaces. Recent works based on unsigned distance function (UDF) are proposed to handle both watertight and single-layered open surfaces. Nonetheless, as UDF is signless, its direct output is limited to the...Show More

HSDF: Hybrid Sign and Distance Field for Neural Representation of Surfaces with Arbitrary Topologies

Li Wang;Yu-Tao Liu;Jie Yang;Weikai Chen;Xiaoxu Meng;Bo Yang;Jintao Li;Lin Gao

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Early Access Article |

NeRF-Texture: Synthesizing Neural Radiance Field Textures

Yi-Hua Huang;Yan-Pei Cao;Yu-Kun Lai;Ying Shan;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2024 | Volume: 46, Issue: 9 | Journal Article |

Cited by: Papers (1)

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Texture synthesis is a fundamental problem in computer graphics that would benefit various applications. Existing methods are effective in handling 2D image textures. In contrast, many real-world textures contain meso-structure in the 3D geometry space, such as grass, leaves, and fabrics, which cannot be effectively modeled using only 2D image textures. We propose a novel texture synthesis method ...Show More

NeRF-Texture: Synthesizing Neural Radiance Field Textures

Yi-Hua Huang;Yan-Pei Cao;Yu-Kun Lai;Ying Shan;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2024 | Volume: 46, Issue: 9 | Journal Article |

Text2Face: Text-Based Face Generation With Geometry and Appearance Control

Zhaoyang Zhang;Junliang Chen;Hongbo Fu;Jianjun Zhao;Shu-Yu Chen;Lin Gao

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 9 | Journal Article |

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Recent years have witnessed the emergence of various techniques proposed for text-based human face generation and manipulation. Such methods, targeting bridging the semantic gap between text and visual contents, provide users with a deft hand to turn ideas into visuals via text interface and enable more diversified multimedia applications. However, due to the flexibility of linguistic expressivene...Show More

Text2Face: Text-Based Face Generation With Geometry and Appearance Control

Zhaoyang Zhang;Junliang Chen;Hongbo Fu;Jianjun Zhao;Shu-Yu Chen;Lin Gao

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 9 | Journal Article |

Sketch Beautification: Learning Part Beautification and Structure Refinement for Sketches of Man-Made Objects

Deng Yu;Manfred Lau;Lin Gao;Hongbo Fu

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 9 | Journal Article |

Cited by: Papers (1)

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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 structurally. Beautifying a sketch is challenging because of its highly abstract and heavily diverse drawing manner. Existing methods are usually confined to their limited training samples and thus cannot beautify freely dr...Show More

Sketch Beautification: Learning Part Beautification and Structure Refinement for Sketches of Man-Made Objects

Deng Yu;Manfred Lau;Lin Gao;Hongbo Fu

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 9 | Journal Article |

NeUDF: Learning Neural Unsigned Distance Fields With Volume Rendering

Yu-Tao Liu;Li Wang;Jie Yang;Weikai Chen;Xiaoxu Meng;Bo Yang;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2024 | Volume: 46, Issue: 4 | Journal Article |

Cited by: Papers (1)

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Multi-view shape reconstruction has achieved impressive progresses thanks to the latest advances in the neural implicit rendering. However, existing methods based on signed distance function (SDF) are limited to closed surfaces, failing to reconstruct a wide range of real-world objects that contain open-surface structures. In this work, we introduce a new neural rendering framework, coded NeUDF, t...Show More

NeUDF: Learning Neural Unsigned Distance Fields With Volume Rendering

Yu-Tao Liu;Li Wang;Jie Yang;Weikai Chen;Xiaoxu Meng;Bo Yang;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2024 | Volume: 46, Issue: 4 | Journal Article |

LC-NeRF: Local Controllable Face Generation in Neural Radiance Field

Wen-Yang Zhou;Lu Yuan;Shu-Yu Chen;Lin Gao;Shi-Min Hu

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 8 | Journal Article |

Cited by: Papers (2)

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3D face generation has achieved high visual quality and 3D consistency thanks to the development of neural radiance fields (NeRF). However, these methods model the whole face as a neural radiance field, which limits the controllability of the local regions. In other words, previous methods struggle to independently control local regions, such as the mouth, nose, and hair. To improve local controll...Show More

LC-NeRF: Local Controllable Face Generation in Neural Radiance Field

Wen-Yang Zhou;Lu Yuan;Shu-Yu Chen;Lin Gao;Shi-Min Hu

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 8 | Journal Article |

Keyframe Control of Music-Driven 3D Dance Generation

Zhipeng Yang;Yu-Hui Wen;Shu-Yu Chen;Xiao Liu;Yuan Gao;Yong-Jin Liu;Lin Gao;Hongbo Fu

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 7 | Journal Article |

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For 3D animators, choreography with artificial intelligence has attracted more attention recently. However, most existing deep learning methods mainly rely on music for dance generation and lack sufficient control over generated dance motions. To address this issue, we introduce the idea of keyframe interpolation for music-driven dance generation and present a novel transition generation technique...Show More

Keyframe Control of Music-Driven 3D Dance Generation

Zhipeng Yang;Yu-Hui Wen;Shu-Yu Chen;Xiao Liu;Yuan Gao;Yong-Jin Liu;Lin Gao;Hongbo Fu

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 7 | Journal Article |

Identity-Aware and Shape-Aware Propagation of Face Editing in Videos

Yue-Ren Jiang;Shu-Yu Chen;Hongbo Fu;Lin Gao

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 7 | Journal Article |

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The development of deep generative models has inspired various facial image editing methods, but many of them are difficult to be directly applied to video editing due to various challenges ranging from imposing 3D constraints, preserving identity consistency, ensuring temporal coherence, etc. To address these challenges, we propose a new framework operating on the StyleGAN2 latent space for ident...Show More

Identity-Aware and Shape-Aware Propagation of Face Editing in Videos

Yue-Ren Jiang;Shu-Yu Chen;Hongbo Fu;Lin Gao

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 7 | Journal Article |

SAC-GAN: Structure-Aware Image Composition

Hang Zhou;Rui Ma;Ling-Xiao Zhang;Lin Gao;Ali Mahdavi-Amiri;Hao Zhang

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 7 | Journal Article |

Cited by: Papers (3)

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We introduce an end-to-end learning framework for image-to-image composition, aiming to plausibly compose an object represented as a cropped patch from an object image into a background scene image. As our approach emphasizes more on semantic and structural coherence of the composed images, rather than their pixel-level RGB accuracies, we tailor the input and output of our network with structure-a...Show More

SAC-GAN: Structure-Aware Image Composition

Hang Zhou;Rui Ma;Ling-Xiao Zhang;Lin Gao;Ali Mahdavi-Amiri;Hao Zhang

IEEE Transactions on Visualization and Computer Graphics

Year: 2024 | Volume: 30, Issue: 7 | Journal Article |

Cambricon-R: A Fully Fused Accelerator for Real-Time Learning of Neural Scene Representation

Xinkai Song;Yuanbo Wen;Xing Hu;Tianbo Liu;Yifan Hao;Haoxuan Zhou;Husheng Han;Tian Zhi;Zidong Du;Wei Li;Rui Zhang;Chen Zhang;Lin Gao;Qi Guo;Tianshi Chen

2023 56th IEEE/ACM International Symposium on Microarchitecture (MICRO)

Year: 2023 | Conference Paper |

Cited by: Papers (4)

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Neural scene representation (NSR) initiates a new methodology of encoding a 3D scene with neural networks by learning from dozens of photos taken from different camera positions. NSR not only achieves significant improvement in the quality of novel view synthesis and 3D reconstruction but also reduces the camera cost from the expensive laser cameras to the cheap color cameras on the shelf. However...Show More

Cambricon-R: A Fully Fused Accelerator for Real-Time Learning of Neural Scene Representation

Xinkai Song;Yuanbo Wen;Xing Hu;Tianbo Liu;Yifan Hao;Haoxuan Zhou;Husheng Han;Tian Zhi;Zidong Du;Wei Li;Rui Zhang;Chen Zhang;Lin Gao;Qi Guo;Tianshi Chen

2023 56th IEEE/ACM International Symposium on Microarchitecture (MICRO)

Year: 2023 | Conference Paper |

E3Sym: Leveraging E(3) Invariance for Unsupervised 3D Planar Reflective Symmetry Detection

Ren-Wu Li;Ling-Xiao Zhang;Chunpeng Li;Yu-Kun Lai;Lin Gao

2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Year: 2023 | Conference Paper |

Cited by: Papers (1)

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Detecting symmetrical properties is a fundamental task in 3D shape analysis. In the case of a 3D model with planar symmetries, each point has a corresponding mirror point w.r.t. a symmetry plane, and the correspondences remain invariant under any arbitrary Euclidean transformation. Our proposed method, E3Sym, aims to detect planar reflective symmetry in an unsupervised and end-to-end manner by lev...Show More

E3Sym: Leveraging E(3) Invariance for Unsupervised 3D Planar Reflective Symmetry Detection

Ren-Wu Li;Ling-Xiao Zhang;Chunpeng Li;Yu-Kun Lai;Lin Gao

2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Year: 2023 | Conference Paper |

Interactive NeRF Geometry Editing With Shape Priors

Yu-Jie Yuan;Yang-Tian Sun;Yu-Kun Lai;Yuewen Ma;Rongfei Jia;Leif Kobbelt;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 12 | Journal Article |

Cited by: Papers (2)

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Neural Radiance Fields (NeRFs) have shown great potential for tasks like novel view synthesis of static 3D scenes. Since NeRFs are trained on a large number of input images, it is not trivial to change their content afterwards. Previous methods to modify NeRFs provide some control but they do not support direct shape deformation which is common for geometry representations like triangle meshes. In...Show More

Interactive NeRF Geometry Editing With Shape Priors

Yu-Jie Yuan;Yang-Tian Sun;Yu-Kun Lai;Yuewen Ma;Rongfei Jia;Leif Kobbelt;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 12 | Journal Article |

STAR-TM: STructure Aware Reconstruction of Textured Mesh From Single Image

Tong Wu;Lin Gao;Ling-Xiao Zhang;Yu-Kun Lai;Hao Zhang

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 12 | Journal Article |

Cited by: Papers (1)

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We present a novel method for single-view 3D reconstruction of textured meshes, with a focus to address the primary challenge surrounding texture inference and transfer. Our key observation is that learning textured reconstruction in a structure-aware and globally consistent manner is effective in handling the severe ill-posedness of the texturing problem and significant variations in object pose ...Show More

STAR-TM: STructure Aware Reconstruction of Textured Mesh From Single Image

Tong Wu;Lin Gao;Ling-Xiao Zhang;Yu-Kun Lai;Hao Zhang

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 12 | Journal Article |

NeUDF: Leaning Neural Unsigned Distance Fields with Volume Rendering

Yu-Tao Liu;Li Wang;Jie Yang;Weikai Chen;Xiaoxu Meng;Bo Yang;Lin Gao

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2023 | Conference Paper |

Cited by: Papers (22)

HTML

Multi-view shape reconstruction has achieved impressive progresses thanks to the latest advances in neural implicit surface rendering. However, existing methods based on signed distance function (SDF) are limited to closed surfaces, failing to reconstruct a wide range of real-world objects that contain open-surface structures. In this work, we introduce a new neural rendering framework, coded NeUD...Show More

NeUDF: Leaning Neural Unsigned Distance Fields with Volume Rendering

Yu-Tao Liu;Li Wang;Jie Yang;Weikai Chen;Xiaoxu Meng;Bo Yang;Lin Gao

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2023 | Conference Paper |

GLIM-Net: Chronic Glaucoma Forecast Transformer for Irregularly Sampled Sequential Fundus Images

Xiaoyan Hu;Ling-Xiao Zhang;Lin Gao;Weiwei Dai;Xiaoguang Han;Yu-Kun Lai;Yiqiang Chen

IEEE Transactions on Medical Imaging

Year: 2023 | Volume: 42, Issue: 6 | Journal Article |

Cited by: Papers (9)

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Chronic Glaucoma is an eye disease with progressive optic nerve damage. It is the second leading cause of blindness after cataract and the first leading cause of irreversible blindness. Glaucoma forecast can predict future eye state of a patient by analyzing the historical fundus images, which is helpful for early detection and intervention of potential patients and avoiding the outcome of blindne...Show More

GLIM-Net: Chronic Glaucoma Forecast Transformer for Irregularly Sampled Sequential Fundus Images

Xiaoyan Hu;Ling-Xiao Zhang;Lin Gao;Weiwei Dai;Xiaoguang Han;Yu-Kun Lai;Yiqiang Chen

IEEE Transactions on Medical Imaging

Year: 2023 | Volume: 42, Issue: 6 | Journal Article |

SceneHGN: Hierarchical Graph Networks for 3D Indoor Scene Generation With Fine-Grained Geometry

Lin Gao;Jia-Mu Sun;Kaichun Mo;Yu-Kun Lai;Leonidas J. Guibas;Jie Yang

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 7 | Journal Article |

Cited by: Papers (13)

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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, including room layout, as well as furniture type, geometry, and placement. High-quality 3D indoor scenes are highly demanded while it requires expertise and is time-consuming to design high-quality 3D indoor scenes man...Show More

SceneHGN: Hierarchical Graph Networks for 3D Indoor Scene Generation With Fine-Grained Geometry

Lin Gao;Jia-Mu Sun;Kaichun Mo;Yu-Kun Lai;Leonidas J. Guibas;Jie Yang

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 7 | Journal Article |

Neural Radiance Fields From Sparse RGB-D Images for High-Quality View Synthesis

Yu-Jie Yuan;Yu-Kun Lai;Yi-Hua Huang;Leif Kobbelt;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 7 | Journal Article |

Cited by: Papers (8)

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The recently proposed neural radiance fields (NeRF) use a continuous function formulated as a multi-layer perceptron (MLP) to model the appearance and geometry of a 3D scene. This enables realistic synthesis of novel views, even for scenes with view dependent appearance. Many follow-up works have since extended NeRFs in different ways. However, a fundamental restriction of the method remains that ...Show More

Neural Radiance Fields From Sparse RGB-D Images for High-Quality View Synthesis

Yu-Jie Yuan;Yu-Kun Lai;Yi-Hua Huang;Leif Kobbelt;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 7 | Journal Article |

Human Motion Transfer With 3D Constraints and Detail Enhancement

Yang-Tian Sun;Qian-Cheng Fu;Yue-Ren Jiang;Zitao Liu;Yu-Kun Lai;Hongbo Fu;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 4 | Journal Article |

Cited by: Papers (5)

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We propose a new method for realistic human motion transfer using a generative adversarial network (GAN), which generates a motion video of a target character imitating actions of a source character, while maintaining high authenticity of the generated results. We tackle the problem by decoupling and recombining the posture information and appearance information of both the source and target chara...Show More

Human Motion Transfer With 3D Constraints and Detail Enhancement

Yang-Tian Sun;Qian-Cheng Fu;Yue-Ren Jiang;Zitao Liu;Yu-Kun Lai;Hongbo Fu;Lin Gao

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2023 | Volume: 45, Issue: 4 | Journal Article |

DrawingInStyles: Portrait Image Generation and Editing With Spatially Conditioned StyleGAN

Wanchao Su;Hui Ye;Shu-Yu Chen;Lin Gao;Hongbo Fu

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 10 | Journal Article |

Cited by: Papers (9)

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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-the-art generation ability but the original StyleGAN is not friendly for sketch-based creation due to its unconditional generation nature. To address this issue, we propose a direct conditioning strategy to better preserv...Show More

DrawingInStyles: Portrait Image Generation and Editing With Spatially Conditioned StyleGAN

Wanchao Su;Hui Ye;Shu-Yu Chen;Lin Gao;Hongbo Fu

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 10 | Journal Article |

Learning-Based Intrinsic Reflectional Symmetry Detection

Yi-Ling Qiao;Lin Gao;Shu-Zhi Liu;Ligang Liu;Yu-Kun Lai;Xilin Chen

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 9 | Journal Article |

Cited by: Papers (2)

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Reflectional symmetry is a ubiquitous pattern in nature. Previous works usually solve this problem by voting or sampling, suffering from high computational cost and randomness. In this article, we propose a learning-based approach to intrinsic reflectional symmetry detection. Instead of directly finding symmetric point pairs, we parametrize this self-isometry using a functional map matrix, which c...Show More

Learning-Based Intrinsic Reflectional Symmetry Detection

Yi-Ling Qiao;Lin Gao;Shu-Zhi Liu;Ligang Liu;Yu-Kun Lai;Xilin Chen

IEEE Transactions on Visualization and Computer Graphics

Year: 2023 | Volume: 29, Issue: 9 | Journal Article |

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