67 citations · 174 across the 25 of their papers we have counts for
29 papers
Efficient 3D Articulated Human Generation with Layered Surface Volumes
Yinghao Xu, Wang Yifan, Alexander W. Bergman +3
Access to high-quality and diverse 3D articulated digital human assets is crucial in various applications, ranging from virtual reality to social platforms. Generative approaches,…
Invertible Neural Skinning
Yash Kant, Aliaksandr Siarohin, Riza Alp Guler +4
Building animatable and editable models of clothed humans from raw 3D scans and poses is a challenging problem. Existing reposing methods suffer from the limited expressiveness of…
AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control
Ruixiang Jiang, Can Wang, Jingbo Zhang +4
Neural implicit fields are powerful for representing 3D scenes and generating high-quality novel views, but it remains challenging to use such implicit representations for creating…
Unsupervised Volumetric Animation
Aliaksandr Siarohin, Willi Menapace, Ivan Skorokhodov +5
We propose a novel approach for unsupervised 3D animation of non-rigid deformable objects. Our method learns the 3D structure and dynamics of objects solely from single-view RGB vi…
InfiniCity: Infinite-Scale City Synthesis
Chieh Hubert Lin, Hsin-Ying Lee, Willi Menapace +4
Toward infinite-scale 3D city synthesis, we propose a novel framework, InfiniCity, which constructs and renders an unconstrainedly large and 3D-grounded environment from random noi…
3DAvatarGAN: Bridging Domains for Personalized Editable Avatars
Rameen Abdal, Hsin-Ying Lee, Peihao Zhu +4
Modern 3D-GANs synthesize geometry and texture by training on large-scale datasets with a consistent structure. Training such models on stylized, artistic data, with often unknown,…
DisCoScene: Spatially Disentangled Generative Radiance Fields for Controllable 3D-aware Scene Synthesis
Yinghao Xu, Menglei Chai, Zifan Shi +8
Existing 3D-aware image synthesis approaches mainly focus on generating a single canonical object and show limited capacity in composing a complex scene containing a variety of obj…
NeRF-Art: Text-Driven Neural Radiance Fields Stylization
Can Wang, Ruixiang Jiang, Menglei Chai +3
As a powerful representation of 3D scenes, the neural radiance field (NeRF) enables high-quality novel view synthesis from multi-view images. Stylizing NeRF, however, remains chall…
Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNN
Yadi Cao, Menglei Chai, Minchen Li +1
Learning the physical simulation on large-scale meshes with flat Graph Neural Networks (GNNs) and stacking Message Passings (MPs) is challenging due to the scaling complexity w.r.t…
Cross-Modal 3D Shape Generation and Manipulation
Zezhou Cheng, Menglei Chai, Jian Ren +5
Creating and editing the shape and color of 3D objects require tremendous human effort and expertise. Compared to direct manipulation in 3D interfaces, 2D interactions such as sket…
Quantized GAN for Complex Music Generation from Dance Videos
Ye Zhu, Kyle Olszewski, Yu Wu +4
We present Dance2Music-GAN (D2M-GAN), a novel adversarial multi-modal framework that generates complex musical samples conditioned on dance videos. Our proposed framework takes dan…
R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis
Huan Wang, Jian Ren, Zeng Huang +4
Recent research explosion on Neural Radiance Field (NeRF) shows the encouraging potential to represent complex scenes with neural networks. One major drawback of NeRF is its prohib…
NeROIC: Neural Rendering of Objects from Online Image Collections
Zhengfei Kuang, Kyle Olszewski, Menglei Chai +3
We present a novel method to acquire object representations from online image collections, capturing high-quality geometry and material properties of arbitrary objects from photogr…
CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields
Can Wang, Menglei Chai, Mingming He +2
We present CLIP-NeRF, a multi-modal 3D object manipulation method for neural radiance fields (NeRF). By leveraging the joint language-image embedding space of the recent Contrastiv…
DisUnknown: Distilling Unknown Factors for Disentanglement Learning
Sitao Xiang, Yuming Gu, Pengda Xiang +4
Disentangling data into interpretable and independent factors is critical for controllable generation tasks. With the availability of labeled data, supervision can help enforce the…
Flow Guided Transformable Bottleneck Networks for Motion Retargeting
Jian Ren, Menglei Chai, Oliver J. Woodford +2
Human motion retargeting aims to transfer the motion of one person in a "driving" video or set of images to another person. Existing efforts leverage a long training video from eac…
A Good Image Generator Is What You Need for High-Resolution Video Synthesis
Yu Tian, Jian Ren, Menglei Chai +4
Image and video synthesis are closely related areas aiming at generating content from noise. While rapid progress has been demonstrated in improving image-based models to handle la…
Exemplar-Based 3D Portrait Stylization
Fangzhou Han, Shuquan Ye, Mingming He +2
Exemplar-based portrait stylization is widely attractive and highly desired. Despite recent successes, it remains challenging, especially when considering both texture and geometri…
Motion Representations for Articulated Animation
Aliaksandr Siarohin, Oliver J. Woodford, Jian Ren +2
We propose novel motion representations for animating articulated objects consisting of distinct parts. In a completely unsupervised manner, our method identifies object parts, tra…
Cross-Domain and Disentangled Face Manipulation with 3D Guidance
Can Wang, Menglei Chai, Mingming He +2
Face image manipulation via three-dimensional guidance has been widely applied in various interactive scenarios due to its semantically-meaningful understanding and user-friendly c…
Diverse Semantic Image Synthesis via Probability Distribution Modeling
Zhentao Tan, Menglei Chai, Dongdong Chen +5
Semantic image synthesis, translating semantic layouts to photo-realistic images, is a one-to-many mapping problem. Though impressive progress has been recently made, diverse seman…
Efficient Semantic Image Synthesis via Class-Adaptive Normalization
Zhentao Tan, Dongdong Chen, Qi Chu +6
Spatially-adaptive normalization (SPADE) is remarkably successful recently in conditional semantic image synthesis \cite{park2019semantic}, which modulates the normalized activatio…
MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait Editing
Zhentao Tan, Menglei Chai, Dongdong Chen +5
Despite the recent success of face image generation with GANs, conditional hair editing remains challenging due to the under-explored complexity of its geometry and appearance. In…
Interactive Video Stylization Using Few-Shot Patch-Based Training
Ondřej Texler, David Futschik, Michal Kučera +5
In this paper, we present a learning-based method to the keyframe-based video stylization that allows an artist to propagate the style from a few selected keyframes to the rest of…