25 citations · 44 across the 22 of their papers we have counts for
24 papers
ScenePlacer: Reformulating Scene-Level Object Pose Estimation as Visibility Field Learning
Ken Deng, Jiarui Liu, Guibiao Liao +7
We present ScenePlacer, a framework for scene-level pose estimation of objects generated by state-of-the-art native shape generation models, placing generated 3D objects into scene…
How to Build Digital Humans? From Priors to Photorealistic Avatars
Wojciech Zielonka, Tobias Kirschstein, Timo Bolkart +8
This state-of-the-art report provides an overview of controllable 3D human avatar creation. We describe current 3D avatar systems, which typically consist of three stages: (i) lear…
Mix3R: Mixing Feed-forward Reconstruction and Generative 3D Priors for Joint Multi-view Aligned 3D Reconstruction and Pose Estimation
Siyou Lin, Zhou Xue, Hongwen Zhang +4
Recent trends in sparse-view 3D reconstruction have taken two different paths: feed-forward reconstruction that predicts pixel-aligned point maps without a complete geometry, and g…
GeoDiff4D: Geometry-Aware Diffusion for 4D Head Avatar Reconstruction
Chao Xu, Xiaochen Zhao, Xiang Deng +4
Reconstructing photorealistic and animatable 4D head avatars from a single portrait image remains a fundamental challenge in computer vision. While diffusion models have enabled re…
U-Mind: A Unified Framework for Real-Time Multimodal Interaction with Audiovisual Generation
Xiang Deng, Feng Gao, Yong Zhang +5
Full-stack multimodal interaction in real-time is a central goal in building intelligent embodied agents capable of natural, dynamic communication. However, existing systems are ei…
FlexAvatar: Flexible Large Reconstruction Model for Animatable Gaussian Head Avatars with Detailed Deformation
Cheng Peng, Zhuo Su, Liao Wang +7
We present FlexAvatar, a flexible large reconstruction model for high-fidelity 3D head avatars with detailed dynamic deformation from single or sparse images, without requiring cam…
DevilSight: Augmenting Monocular Human Avatar Reconstruction through a Virtual Perspective
Yushuo Chen, Ruizhi Shao, Youxin Pang +4
We present a novel framework to reconstruct human avatars from monocular videos. Recent approaches have struggled either to capture the fine-grained dynamic details from the input…
Parametric Gaussian Human Model: Generalizable Prior for Efficient and Realistic Human Avatar Modeling
Cheng Peng, Jingxiang Sun, Yushuo Chen +3
Photorealistic and animatable human avatars are a key enabler for virtual/augmented reality, telepresence, and digital entertainment. While recent advances in 3D Gaussian Splatting…
Stereo-Talker: Audio-driven 3D Human Synthesis with Prior-Guided Mixture-of-Experts
Xiang Deng, Youxin Pang, Xiaochen Zhao +6
This paper introduces Stereo-Talker, a novel one-shot audio-driven human video synthesis system that generates 3D talking videos with precise lip synchronization, expressive body g…
MeshAvatar: Learning High-quality Triangular Human Avatars from Multi-view Videos
Yushuo Chen, Zerong Zheng, Zhe Li +2
We present a novel pipeline for learning high-quality triangular human avatars from multi-view videos. Recent methods for avatar learning are typically based on neural radiance fie…
GPHM: Gaussian Parametric Head Model for Monocular Head Avatar Reconstruction
Yuelang Xu, Zhaoqi Su, Qingyao Wu +1
Creating high-fidelity 3D human head avatars is crucial for applications in VR/AR, digital human, and film production. Recent advances have leveraged morphable face models to gener…
LayGA: Layered Gaussian Avatars for Animatable Clothing Transfer
Siyou Lin, Zhe Li, Zhaoqi Su +3
Animatable clothing transfer, aiming at dressing and animating garments across characters, is a challenging problem. Most human avatar works entangle the representations of the hum…
TexVocab: Texture Vocabulary-conditioned Human Avatars
Yuxiao Liu, Zhe Li, Yebin Liu +1
To adequately utilize the available image evidence in multi-view video-based avatar modeling, we propose TexVocab, a novel avatar representation that constructs a texture vocabular…
MonoGaussianAvatar: Monocular Gaussian Point-based Head Avatar
Yufan Chen, Lizhen Wang, Qijing Li +4
The ability to animate photo-realistic head avatars reconstructed from monocular portrait video sequences represents a crucial step in bridging the gap between the virtual and real…
GMTalker: Gaussian Mixture-based Audio-Driven Emotional Talking Video Portraits
Yibo Xia, Lizhen Wang, Xiang Deng +3
Synthesizing high-fidelity and emotion-controllable talking video portraits, with audio-lip sync, vivid expressions, realistic head poses, and eye blinks, has been an important and…
HHAvatar: Gaussian Head Avatar with Dynamic Hairs
Zhanfeng Liao, Yuelang Xu, Zhe Li +6
Creating high-fidelity 3D head avatars has always been a research hotspot, but it remains a great challenge under lightweight sparse view setups. In this paper, we propose HHAvatar…
InvertAvatar: Incremental GAN Inversion for Generalized Head Avatars
Xiaochen Zhao, Jingxiang Sun, Lizhen Wang +2
While high fidelity and efficiency are central to the creation of digital head avatars, recent methods relying on 2D or 3D generative models often experience limitations such as sh…
GPS-Gaussian: Generalizable Pixel-wise 3D Gaussian Splatting for Real-time Human Novel View Synthesis
Shunyuan Zheng, Boyao Zhou, Ruizhi Shao +4
We present a new approach, termed GPS-Gaussian, for synthesizing novel views of a character in a real-time manner. The proposed method enables 2K-resolution rendering under a spars…
HumanNorm: Learning Normal Diffusion Model for High-quality and Realistic 3D Human Generation
Xin Huang, Ruizhi Shao, Qi Zhang +4
Recent text-to-3D methods employing diffusion models have made significant advancements in 3D human generation. However, these approaches face challenges due to the limitations of…
Animatable and Relightable Gaussians for High-fidelity Human Avatar Modeling
Zhe Li, Yipengjing Sun, Zerong Zheng +3
Modeling animatable human avatars from RGB videos is a long-standing and challenging problem. Recent works usually adopt MLP-based neural radiance fields (NeRF) to represent 3D hum…
DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
Jingxiang Sun, Bo Zhang, Ruizhi Shao +4
We present DreamCraft3D, a hierarchical 3D content generation method that produces high-fidelity and coherent 3D objects. We tackle the problem by leveraging a 2D reference image t…
High-Fidelity 3D Head Avatars Reconstruction through Spatially-Varying Expression Conditioned Neural Radiance Field
Minghan Qin, Yifan Liu, Yuelang Xu +3
One crucial aspect of 3D head avatar reconstruction lies in the details of facial expressions. Although recent NeRF-based photo-realistic 3D head avatar methods achieve high-qualit…
HAvatar: High-fidelity Head Avatar via Facial Model Conditioned Neural Radiance Field
Xiaochen Zhao, Lizhen Wang, Jingxiang Sun +3
The problem of modeling an animatable 3D human head avatar under light-weight setups is of significant importance but has not been well solved. Existing 3D representations either p…
Control4D: Efficient 4D Portrait Editing with Text
Ruizhi Shao, Jingxiang Sun, Cheng Peng +4
We introduce Control4D, an innovative framework for editing dynamic 4D portraits using text instructions. Our method addresses the prevalent challenges in 4D editing, notably the i…