6 papers
UniWorld-Design: From Pixel Generation to Layer-Native Design
Zongjian Li, Zhiyuan Yan, Chenxu Bai +9
We introduce UniWorld-Design, a framework that redefines image generation from flat pixel synthesis to structured visual composition, with semantic RGBA layers as the atomic units…
VEBench:Benchmarking Large Multimodal Models for Real-World Video Editing
Andong Deng, Dawei Du, Zhenfang Chen +7
Real-world video editing demands not only expert knowledge of cinematic techniques but also multimodal reasoning to select, align, and combine footage into coherent narratives. Whi…
Large Language Models are Universal Reasoners for Visual Generation
Sucheng Ren, Chen Chen, Zhenbang Wang +5
Text-to-image generation has advanced rapidly with diffusion models, progressing from CLIP and T5 conditioning to unified systems where a single LLM backbone handles both visual un…
STIV: Scalable Text and Image Conditioned Video Generation
Zongyu Lin, Wei Liu, Chen Chen +13
The field of video generation has made remarkable advancements, yet there remains a pressing need for a clear, systematic recipe that can guide the development of robust and scalab…
GIE-Bench: Towards Grounded Evaluation for Text-Guided Image Editing
Yusu Qian, Jiasen Lu, Tsu-Jui Fu +5
Editing images using natural language instructions has become a natural and expressive way to modify visual content; yet, evaluating the performance of such models remains challeng…
UniVG: A Generalist Diffusion Model for Unified Image Generation and Editing
Tsu-Jui Fu, Yusu Qian, Chen Chen +3
Text-to-Image (T2I) diffusion models have shown impressive results in generating visually compelling images following user prompts. Building on this, various methods further fine-t…