2 citations · 2 across the 4 of their papers we have counts for
4 papers
Evaluating Image Editing with LLMs: A Comprehensive Benchmark and Intermediate-Layer Probing Approach
Shiqi Gao, Zitong Xu, Kang Fu +3
Evaluating text-guided image editing (TIE) methods remains a challenging problem, as reliable assessment should simultaneously consider perceptual quality, alignment with textual i…
Preference-Guided Debiasing for No-Reference Enhancement Image Quality Assessment
Shiqi Gao, Kang Fu, Zitong Xu +4
Current no-reference image quality assessment (NR-IQA) models for enhanced images often struggle to generalize, as they tend to overfit to the distinct patterns of specific enhance…
LMM4Edit: Benchmarking and Evaluating Multimodal Image Editing with LMMs
Zitong Xu, Huiyu Duan, Bingnan Liu +9
The rapid advancement of Text-guided Image Editing (TIE) enables image modifications through text prompts. However, current TIE models still struggle to balance image quality, edit…
Quality-guided Skin Tone Enhancement for Portrait Photography
Shiqi Gao, Huiyu Duan, Xinyue Li +7
In recent years, learning-based color and tone enhancement methods for photos have become increasingly popular. However, most learning-based image enhancement methods just learn a…