110 citations · 194 across the 18 of their papers we have counts for
20 papers
DPoser-X: Diffusion Model as Robust 3D Whole-body Human Pose Prior
Junzhe Lu, Jing Lin, Hongkun Dou +8
We present DPoser-X, a diffusion-based prior model for 3D whole-body human poses. Building a versatile and robust full-body human pose prior remains challenging due to the inherent…
Disco4D: Disentangled 4D Human Generation and Animation from a Single Image
Hui En Pang, Shuai Liu, Zhongang Cai +3
We present \textbf{Disco4D}, a novel Gaussian Splatting framework for 4D human generation and animation from a single image. Different from existing methods, Disco4D distinctively…
AiOS: All-in-One-Stage Expressive Human Pose and Shape Estimation
Qingping Sun, Yanjun Wang, Ailing Zeng +8
Expressive human pose and shape estimation (a.k.a. 3D whole-body mesh recovery) involves the human body, hand, and expression estimation. Most existing methods have tackled this ta…
Towards Robust and Expressive Whole-body Human Pose and Shape Estimation
Hui EnPang, Zhongang Cai, Lei Yang +4
Whole-body pose and shape estimation aims to jointly predict different behaviors (e.g., pose, hand gesture, facial expression) of the entire human body from a monocular image. Exis…
PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generation
Zhaoxi Chen, Fangzhou Hong, Haiyi Mei +3
We present PrimDiffusion, the first diffusion-based framework for 3D human generation. Devising diffusion models for 3D human generation is difficult due to the intensive computati…
ReliTalk: Relightable Talking Portrait Generation from a Single Video
Haonan Qiu, Zhaoxi Chen, Yuming Jiang +5
Recent years have witnessed great progress in creating vivid audio-driven portraits from monocular videos. However, how to seamlessly adapt the created video avatars to other scena…
SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation
Zhongang Cai, Wanqi Yin, Ailing Zeng +10
Expressive human pose and shape estimation (EHPS) unifies body, hands, and face motion capture with numerous applications. Despite encouraging progress, current state-of-the-art me…
PointHPS: Cascaded 3D Human Pose and Shape Estimation from Point Clouds
Zhongang Cai, Liang Pan, Chen Wei +6
Human pose and shape estimation (HPS) has attracted increasing attention in recent years. While most existing studies focus on HPS from 2D images or videos with inherent depth ambi…
IT3D: Improved Text-to-3D Generation with Explicit View Synthesis
Yiwen Chen, Chi Zhang, Xiaofeng Yang +4
Recent strides in Text-to-3D techniques have been propelled by distilling knowledge from powerful large text-to-image diffusion models (LDMs). Nonetheless, existing Text-to-3D appr…
HumanLiff: Layer-wise 3D Human Generation with Diffusion Model
Shoukang Hu, Fangzhou Hong, Tao Hu +5
3D human generation from 2D images has achieved remarkable progress through the synergistic utilization of neural rendering and generative models. Existing 3D human generative mode…
DNA-Rendering: A Diverse Neural Actor Repository for High-Fidelity Human-centric Rendering
Wei Cheng, Ruixiang Chen, Wanqi Yin +18
Realistic human-centric rendering plays a key role in both computer vision and computer graphics. Rapid progress has been made in the algorithm aspect over the years, yet existing…
RenderMe-360: A Large Digital Asset Library and Benchmarks Towards High-fidelity Head Avatars
Dongwei Pan, Long Zhuo, Jingtan Piao +13
Synthesizing high-fidelity head avatars is a central problem for computer vision and graphics. While head avatar synthesis algorithms have advanced rapidly, the best ones still fac…
ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model
Mingyuan Zhang, Xinying Guo, Liang Pan +5
3D human motion generation is crucial for creative industry. Recent advances rely on generative models with domain knowledge for text-driven motion generation, leading to substanti…
SynBody: Synthetic Dataset with Layered Human Models for 3D Human Perception and Modeling
Zhitao Yang, Zhongang Cai, Haiyi Mei +12
Synthetic data has emerged as a promising source for 3D human research as it offers low-cost access to large-scale human datasets. To advance the diversity and annotation quality o…
Zolly: Zoom Focal Length Correctly for Perspective-Distorted Human Mesh Reconstruction
Wenjia Wang, Yongtao Ge, Haiyi Mei +6
As it is hard to calibrate single-view RGB images in the wild, existing 3D human mesh reconstruction (3DHMR) methods either use a constant large focal length or estimate one based…
SHERF: Generalizable Human NeRF from a Single Image
Shoukang Hu, Fangzhou Hong, Liang Pan +3
Existing Human NeRF methods for reconstructing 3D humans typically rely on multiple 2D images from multi-view cameras or monocular videos captured from fixed camera views. However,…
OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generation
Tong Wu, Jiarui Zhang, Xiao Fu +9
Recent advances in modeling 3D objects mostly rely on synthetic datasets due to the lack of large-scale realscanned 3D databases. To facilitate the development of 3D perception, re…
Benchmarking and Analyzing 3D Human Pose and Shape Estimation Beyond Algorithms
Hui En Pang, Zhongang Cai, Lei Yang +2
3D human pose and shape estimation (a.k.a. "human mesh recovery") has achieved substantial progress. Researchers mainly focus on the development of novel algorithms, while less att…
MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model
Mingyuan Zhang, Zhongang Cai, Liang Pan +4
Human motion modeling is important for many modern graphics applications, which typically require professional skills. In order to remove the skill barriers for laymen, recent moti…
AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars
Fangzhou Hong, Mingyuan Zhang, Liang Pan +3
3D avatar creation plays a crucial role in the digital age. However, the whole production process is prohibitively time-consuming and labor-intensive. To democratize this technolog…