11 citations · 12 across the 8 of their papers we have counts for
9 papers · 1 filter
Pico-Banana-400K: A Large-Scale Dataset for Text-Guided Image Editing
Yusu Qian, Eli Bocek-Rivele, Liangchen Song +5
Recent advances in multimodal models have demonstrated remarkable text-guided image editing capabilities, with systems like GPT-4o and Nano-Banana setting new benchmarks. However,…
MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer
Yanghao Li, Rui Qian, Bowen Pan +24
Unified multimodal Large Language Models (LLMs) that can both understand and generate visual content hold immense potential. However, existing open-source models often suffer from…
Score Distillation of Flow Matching Models
Mingyuan Zhou, Yi Gu, Huangjie Zheng +5
Diffusion models achieve high-quality image generation but are limited by slow iterative sampling. Distillation methods alleviate this by enabling one- or few-step generation. Flow…
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…
DiT-Air: Revisiting the Efficiency of Diffusion Model Architecture Design in Text to Image Generation
Chen Chen, Rui Qian, Wenze Hu +8
In this work, we empirically study Diffusion Transformers (DiTs) for text-to-image generation, focusing on architectural choices, text-conditioning strategies, and training protoco…
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…
Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Zhengfeng Lai, Vasileios Saveris, Chen Chen +9
Recent advancements in multimodal models highlight the value of rewritten captions for improving performance, yet key challenges remain. For example, while synthetic captions often…
Guiding Instruction-based Image Editing via Multimodal Large Language Models
Tsu-Jui Fu, Wenze Hu, Xianzhi Du +3
Instruction-based image editing improves the controllability and flexibility of image manipulation via natural commands without elaborate descriptions or regional masks. However, h…