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Wenhan Zhu

11 accepted papers

2025

Multimodal Latent Diffusion Model for Complex Sewing Pattern Generation

ICCV 2025poster

Generating sewing patterns in garment design is receiving increasing attention due to its CG-friendly and flexible-editing nature. Previous sewing pattern generation methods have been able to produce exquisite clothing, but struggle to design complex garments with detailed control. To address these…

Cited by 0SourcePDFScholar
2025

S^3-Face: SSS-Compliant Facial Reflectance Estimation via Diffusion Priors

CVPR 2025poster

Recent 3D face reconstruction methods have made remarkable advancements, yet achieving high-quality facial reflectance from monocular input remains challenging. Existing methods rely on the light-stage captured data to learn facial reflectance models. However, limited subject diversity in these data…

Cited by 0SourcePDFScholar
2025

Towards High-fidelity 3D Talking Avatar with Personalized Dynamic Texture

CVPR 2025poster

Significant progress has been made for speech-driven 3D face animation, but most works focus on learning the motion of mesh/geometry, ignoring the impact of dynamic texture. In this work, we reveal that dynamic texture plays a key role in rendering high-fidelity talking avatars, and introduce a high…

2024

3D-Aware Face Editing via Warping-Guided Latent Direction Learning

CVPR 2024poster

3D facial editing a longstanding task in computer vision with broad applications is expected to fast and intuitively manipulate any face from arbitrary viewpoints following the user's will. Existing works have limitations in terms of intuitiveness generalization and efficiency. To overcome these cha…

2024

Monocular Identity-Conditioned Facial Reflectance Reconstruction

CVPR 2024poster

Recent 3D face reconstruction methods have made remarkable advancements yet there remain huge challenges in monocular high-quality facial reflectance reconstruction. Existing methods rely on a large amount of light-stage captured data to learn facial reflectance models. However the lack of subject d…

Cited by 3SourcePDFScholar
2024

ReGenNet: Towards Human Action-Reaction Synthesis

CVPR 2024poster

Humans constantly interact with their surrounding environments. Current human-centric generative models mainly focus on synthesizing humans plausibly interacting with static scenes and objects while the dynamic human action-reaction synthesis for ubiquitous causal human-human interactions is less ex…

2024

Topo4D: Topology-Preserving Gaussian Splatting for High-Fidelity 4D Head Capture

ECCV 2024poster

"Recent significant advances in high-quality face reconstruction have been made, but challenges remain in 4D face asset reconstruction. 4D head capture aims to generate dynamic topological meshes and corresponding texture maps from videos, which is widely utilized in movies and games for its ability…

2023

GANHead: Towards Generative Animatable Neural Head Avatars

CVPR 2023poster

To bring digital avatars into people's lives, it is highly demanded to efficiently generate complete, realistic, and animatable head avatars. This task is challenging, and it is difficult for existing methods to satisfy all the requirements at once. To achieve these goals, we propose GANHead (Genera…

Cited by 20SourcePDFScholar
2023

NeRF-IBVS: Visual Servo Based on NeRF for Visual Localization and Navigation

NeurIPS 2023poster

Visual localization is a fundamental task in computer vision and robotics. Training existing visual localization methods requires a large number of posed images to generalize to novel views, while state-of-the-art methods generally require dense ground truth 3D labels for supervision. However, acqui…

Cited by 9SourcePDFScholar
2021

Perceptual Quality Assessment for Recognizing True and Pseudo 4k Content

ICASSP 2021accepted

To meet the imperative demand for monitoring the quality of Ultra High-Definition (UHD) content in multimedia industries, we propose an efficient no-reference (NR) image quality assessment (IQA) metric to distinguish original and pseudo 4K contents and measure the quality of their quality in this pa…

Cited by 0SourceScholar