most citedSketch2PoseNet: Efficient and Generalized Sketch to 3D Human Pose Prediction

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2025

Pressure2Motion: Hierarchical Human Motion Reconstruction from Ground Pressure with Text Guidance

Zhengxuan Li, Qinhui Yang, Yiyu Zhuang +7

We present Pressure2Motion, a novel motion capture algorithm that reconstructs human motion from a ground pressure sequence and text prompt. At inference time, Pressure2Motion requ…

cs.CV20251 cited

Sketch2PoseNet: Efficient and Generalized Sketch to 3D Human Pose Prediction

Li Wang, Yiyu Zhuang, Yanwen Wang +4

3D human pose estimation from sketches has broad applications in computer animation and film production. Unlike traditional human pose estimation, this task presents unique challen…

cs.CV2025

TeRA: Rethinking Text-guided Realistic 3D Avatar Generation

Yanwen Wang, Yiyu Zhuang, Jiawei Zhang +5

In this paper, we rethink text-to-avatar generative models by proposing TeRA, a more efficient and effective framework than the previous SDS-based models and general large 3D gener…

cs.CV2024

MCMat: Multiview-Consistent and Physically Accurate PBR Material Generation

Shenhao Zhu, Lingteng Qiu, Xiaodong Gu +11

Existing 2D methods utilize UNet-based diffusion models to generate multi-view physically-based rendering (PBR) maps but struggle with multi-view inconsistency, while some 3D metho…

cs.CV2024

IDOL: Instant Photorealistic 3D Human Creation from a Single Image

Yiyu Zhuang, Jiaxi Lv, Hao Wen +7

Creating a high-fidelity, animatable 3D full-body avatar from a single image is a challenging task due to the diverse appearance and poses of humans and the limited availability of…

cs.CV2024

FATE: Full-head Gaussian Avatar with Textural Editing from Monocular Video

Jiawei Zhang, Zijian Wu, Zhiyang Liang +5

Reconstructing high-fidelity, animatable 3D head avatars from effortlessly captured monocular videos is a pivotal yet formidable challenge. Although significant progress has been m…