4 papers
ITS3D: Inference-Time Scaling for Text-Guided 3D Diffusion Models
Zhenglin Zhou, Fan Ma, Xiaobo Xia +3
We explore inference-time scaling in text-guided 3D diffusion models to enhance generative quality without additional training. To this end, we introduce ITS3D, a framework that fo…
AnchorFlow: Training-Free 3D Editing via Latent Anchor-Aligned Flows
Zhenglin Zhou, Fan Ma, Chengzhuo Gui +4
Training-free 3D editing aims to modify 3D shapes based on human instructions without model finetuning. It plays a crucial role in 3D content creation. However, existing approaches…
Zero-1-to-A: Zero-Shot One Image to Animatable Head Avatars Using Video Diffusion
Zhenglin Zhou, Fan Ma, Hehe Fan +1
Animatable head avatar generation typically requires extensive data for training. To reduce the data requirements, a natural solution is to leverage existing data-free static avata…
DreamDPO: Aligning Text-to-3D Generation with Human Preferences via Direct Preference Optimization
Zhenglin Zhou, Xiaobo Xia, Fan Ma +3
Text-to-3D generation automates 3D content creation from textual descriptions, which offers transformative potential across various fields. However, existing methods often struggle…