Zekai Gu — accepted AI-conference papers

2026

RefAny3D: 3D Asset-Referenced Diffusion Models for Image Generation

Hanzhuo Huang, Qingyang Bao, Zekai Gu, Zhongshuo Du, Cheng Lin, Yuan Liu +1

ICLR 2026poster

In this paper, we propose a 3D asset-referenced diffusion model for image generation, exploring how to integrate 3D assets into image diffusion models. Existing reference-based image generation methods leverage large-scale pretrained diffusion models and demonstrate strong capability in generating d…

Cited by 0 Source ↗code ↗Scholar ↗

2024

DriveSceneGen: Generating Diverse and Realistic Driving Scenarios From Scratch

Shuo Sun, Zekai Gu, Tianchen Sun, Jiawei Sun, Chengran Yuan, Yuhang Han +2

RA-L 2024

Realistic and diverse traffic scenarios in large quantities are crucial for the development and validation of autonomous driving systems. However, owing to numerous difficulties in the data collection process and the reliance on intensive annotations, real-world datasets lack sufficient quantity and

Cited by 32 Source ↗Scholar ↗