7 citations · 26 across the 15 of their papers we have counts for
20 papers
FlowHMR: Physically Plausible Motion Capture from Video
Zhanke Wang, Chengfeng Zhao, Qing Shuai +8
We present FlowHMR, a framework for recovering physically plausible global 3D human motion from monocular video. Previous learning-based methods typically regress human motion dire…
AESOP: Asymmetric Human-Camera Generation with Translation-Intensity Control
Jingzhong Lin, Zhanke Wang, Heng Li +9
Human motion defines an action, while a camera trajectory determines how it is presented. Camera generation for a given human motion and joint human-camera generation are usually t…
AnimateCanvas: Learning Implicit Motion Planning from Composable Kinematic Cues
Zeyu Ling, Di Kang, Qing Shuai +7
Professional character animation requires both natural motion and precise, versatile control. For example, creators often define the timing of a specified action, control the motio…
WIPES: Wavelet-based Visual Primitives
Wenhao Zhang, Hao Zhu, Delong Wu +4
Pursuing a continuous visual representation that offers flexible frequency modulation and fast rendering speed has recently garnered increasing attention in the fields of 3D vision…
DAGSM: Disentangled Avatar Generation with GS-enhanced Mesh
Jingyu Zhuang, Di Kang, Linchao Bao +2
Text-driven avatar generation has gained significant attention owing to its convenience. However, existing methods typically model the human body with all garments as a single 3D m…
MeGA: Hybrid Mesh-Gaussian Head Avatar for High-Fidelity Rendering and Head Editing
Cong Wang, Di Kang, He-Yi Sun +4
Creating high-fidelity head avatars from multi-view videos is a core issue for many AR/VR applications. However, existing methods usually struggle to obtain high-quality renderings…
Neural Point-based Volumetric Avatar: Surface-guided Neural Points for Efficient and Photorealistic Volumetric Head Avatar
Cong Wang, Di Kang, Yan-Pei Cao +3
Rendering photorealistic and dynamically moving human heads is crucial for ensuring a pleasant and immersive experience in AR/VR and video conferencing applications. However, exist…
Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry
Jiaxu Zhang, Junwu Weng, Di Kang +7
A good motion retargeting cannot be reached without reasonable consideration of source-target differences on both the skeleton and shape geometry levels. In this work, we propose a…
Get3DHuman: Lifting StyleGAN-Human into a 3D Generative Model using Pixel-aligned Reconstruction Priors
Zhangyang Xiong, Di Kang, Derong Jin +4
Fast generation of high-quality 3D digital humans is important to a vast number of applications ranging from entertainment to professional concerns. Recent advances in differentiab…
Audio2Gestures: Generating Diverse Gestures from Audio
Jing Li, Di Kang, Wenjie Pei +4
People may perform diverse gestures affected by various mental and physical factors when speaking the same sentences. This inherent one-to-many relationship makes co-speech gesture…
Learning Audio-Driven Viseme Dynamics for 3D Face Animation
Linchao Bao, Haoxian Zhang, Yue Qian +4
We present a novel audio-driven facial animation approach that can generate realistic lip-synchronized 3D facial animations from the input audio. Our approach learns viseme dynamic…
FFHQ-UV: Normalized Facial UV-Texture Dataset for 3D Face Reconstruction
Haoran Bai, Di Kang, Haoxian Zhang +2
We present a large-scale facial UV-texture dataset that contains over 50,000 high-quality texture UV-maps with even illuminations, neutral expressions, and cleaned facial regions,…
NEURAL MARIONETTE: A Transformer-based Multi-action Human Motion Synthesis System
Weiqiang Wang, Xuefei Zhe, Qiuhong Ke +4
We present a neural network-based system for long-term, multi-action human motion synthesis. The system, dubbed as NEURAL MARIONETTE, can produce high-quality and meaningful motion…
Learning to Construct 3D Building Wireframes from 3D Line Clouds
Yicheng Luo, Jing Ren, Xuefei Zhe +4
Line clouds, though under-investigated in the previous work, potentially encode more compact structural information of buildings than point clouds extracted from multi-view images.…
PIFu for the Real World: A Self-supervised Framework to Reconstruct Dressed Human from Single-view Images
Zhangyang Xiong, Dong Du, Yushuang Wu +4
It is very challenging to accurately reconstruct sophisticated human geometry caused by various poses and garments from a single image. Recently, works based on pixel-aligned impli…
Semi-signed prioritized neural fitting for surface reconstruction from unoriented point clouds
Runsong Zhu, Di Kang, Ka-Hei Hui +6
Reconstructing 3D geometry from \emph{unoriented} point clouds can benefit many downstream tasks. Recent shape modeling methods mostly adopt implicit neural representation to fit a…
REALY: Rethinking the Evaluation of 3D Face Reconstruction
Zenghao Chai, Haoxian Zhang, Jing Ren +5
The evaluation of 3D face reconstruction results typically relies on a rigid shape alignment between the estimated 3D model and the ground-truth scan. We observe that aligning two…
CAR: Class-aware Regularizations for Semantic Segmentation
Ye Huang, Di Kang, Liang Chen +4
Recent segmentation methods, such as OCR and CPNet, utilizing "class level" information in addition to pixel features, have achieved notable success for boosting the accuracy of ex…
NeRFReN: Neural Radiance Fields with Reflections
Yuan-Chen Guo, Di Kang, Linchao Bao +2
Neural Radiance Fields (NeRF) has achieved unprecedented view synthesis quality using coordinate-based neural scene representations. However, NeRF's view dependency can only handle…
Audio2Gestures: Generating Diverse Gestures from Speech Audio with Conditional Variational Autoencoders
Jing Li, Di Kang, Wenjie Pei +4
Generating conversational gestures from speech audio is challenging due to the inherent one-to-many mapping between audio and body motions. Conventional CNNs/RNNs assume one-to-one…