3 citations · 3 across the 4 of their papers we have counts for
4 papers
From Corpora to Co-Evolving Capabilities: Capability-Centric Data Design for Generalist Image Generation
Xingjian Wang, Zhao Wang, Taihang Hu +17
Large-scale image generation has benefited from advances in data scale, quality, rebalancing, and recaptioning, yet conventional pipelines typically optimize task-specific datasets…
Exploring the Performance Frontier of Compact Unified Image Generation Models
Taihang Hu, Zhao Wang, Zuan Gao +20
We present Swift-Image, a compact unified model for text-to-image generation, single-image editing, and multi-image editing. Our goal is to explore how far a relatively small visua…
CPI-Bench: A Comprehensive, Practical and Intelligent Benchmark for Real-World Image Editing
Qinye Zhou, Jun Zheng, Yongchao Du +17
With the rapid advancement of image editing models and their widespread application across various domains, there is an increasingly urgent need to deploy these model capabilities…
Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models
Senmao Li, Joost van de Weijer, Taihang Hu +4
The success of recent text-to-image diffusion models is largely due to their capacity to be guided by a complex text prompt, which enables users to precisely describe the desired c…