1 citations · 1 across the 7 of their papers we have counts for
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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…
Adversarial-Guided Diffusion for Multimodal LLM Attacks
Chengwei Xia, Fan Ma, Ruijie Quan +2
This paper addresses the challenge of generating adversarial image using a diffusion model to deceive multimodal large language models (MLLMs) into generating the targeted response…
Insert Anything: Image Insertion via In-Context Editing in DiT
Wensong Song, Hong Jiang, Zongxing Yang +2
This work presents Insert Anything, a unified framework for reference-based image insertion that seamlessly integrates objects from reference images into target scenes under flexib…
BrainGuard: Privacy-Preserving Multisubject Image Reconstructions from Brain Activities
Zhibo Tian, Ruijie Quan, Fan Ma +2
Reconstructing perceived images from human brain activity forms a crucial link between human and machine learning through Brain-Computer Interfaces. Early methods primarily focused…