1 citations · 1 across the 6 of their papers we have counts for
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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…
Open-vocabulary Object Segmentation with Diffusion Models
Ziyi Li, Qinye Zhou, Xiaoyun Zhang +3
The goal of this paper is to extract the visual-language correspondence from a pre-trained text-to-image diffusion model, in the form of segmentation map, i.e., simultaneously gene…
A Simple Plugin for Transforming Images to Arbitrary Scales
Qinye Zhou, Ziyi Li, Weidi Xie +3
Existing models on super-resolution often specialized for one scale, fundamentally limiting their use in practical scenarios. In this paper, we aim to develop a general plugin that…