activity
20232026
most citedEG4D: Explicit Generation of 4D Object without Score Distillation

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Ani3DHuman: Photorealistic 3D Human Animation with Self-guided Stochastic Sampling

Qi Sun, Can Wang, Jiaxiang Shang +2

Current 3D human animation methods struggle to achieve photorealism: kinematics-based approaches lack non-rigid dynamics (e.g., clothing dynamics), while methods that leverage vide…

cs.CV2024★ 1 cited

EG4D: Explicit Generation of 4D Object without Score Distillation

Qi Sun, Zhiyang Guo, Ziyu Wan +5

In recent years, the increasing demand for dynamic 3D assets in design and gaming applications has given rise to powerful generative pipelines capable of synthesizing high-quality…

cs.CV2024

RaFE: Generative Radiance Fields Restoration

Zhongkai Wu, Ziyu Wan, Jing Zhang +2

NeRF (Neural Radiance Fields) has demonstrated tremendous potential in novel view synthesis and 3D reconstruction, but its performance is sensitive to input image quality, which st…

cs.CV2023★ 1 cited

CAD: Photorealistic 3D Generation via Adversarial Distillation

Ziyu Wan, Despoina Paschalidou, Ian Huang +5

The increased demand for 3D data in AR/VR, robotics and gaming applications, gave rise to powerful generative pipelines capable of synthesizing high-quality 3D objects. Most of the…

cs.CV2023

HeadArtist: Text-conditioned 3D Head Generation with Self Score Distillation

Hongyu Liu, Xuan Wang, Ziyu Wan +4

This work presents HeadArtist for 3D head generation from text descriptions. With a landmark-guided ControlNet serving as the generative prior, we come up with an efficient pipelin…