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Dongnan Gui

4 accepted papers

2025

I2VGuard: Safeguarding Images against Misuse in Diffusion-based Image-to-Video Models

CVPR 2025poster

Recent advances in image-to-video generation have enabled animation of still images and offered pixel-level controllability. While these models hold great potential to transform single images into vivid and dynamic videos, they also carry risks of misuse that could impact privacy, security, and copy…

Cited by 0SourcePDFScholar
2025

Image as a World: Generating Interactive World from Single Image via Panoramic Video Generation

NeurIPS 2025poster

Generating an interactive visual world from a single image is both challenging and practically valuable, as single-view inputs are easy to acquire and align well with prompt-driven applications such as gaming and virtual reality. This paper introduces a novel unified framework, Image as a World (**I…

Cited by 0SourceScholar
2025

MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment

ICML 2025poster

Reinforcement Learning from Human Feedback (RLHF) has shown promise in aligning large language models (LLMs). Yet its reliance on a singular reward model often overlooks the diversity of human preferences. Recent approaches address this limitation by leveraging multi-dimensional feedback to fine-tun…

Cited by 0SourcePDFScholar
2023

GlyphControl: Glyph Conditional Control for Visual Text Generation

NeurIPS 2023poster

Recently, there has been an increasing interest in developing diffusion-based text-to-image generative models capable of generating coherent and well-formed visual text. In this paper, we propose a novel and efficient approach called GlyphControl to address this task. Unlike existing methods that re…