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Xiangfei Sheng

4 accepted papers

2026

Fine-grained Image Aesthetic Assessment: Learning Discriminative Scores from Relative Ranks

CVPR 2026

Image aesthetic assessment (IAA) has extensive applications in content creation, album management, and recommendation systems, etc. In such applications, it is commonly needed to pick out the most aesthetically pleasing image from a series of images with subtle aesthetic variations, a topic we refer

Cited by 0SourcecodeScholar
2026

Fine-grained Image Quality Assessment for Perceptual Image Restoration

AAAI 2026technical

Recent years have witnessed remarkable achievements in perceptual image restoration (IR), creating an urgent demand for accurate image quality assessment (IQA), which is essential for both performance comparison and algorithm optimization. Unfortunately, the existing IQA metrics exhibit inherent wea

Cited by 0SourcePDFScholar
2026

LongT2IBench: A Benchmark for Evaluating Long Text-to-Image Generation with Graph-structured Annotations

AAAI 2026technical

The increasing popularity of long Text-to-Image (T2I) generation has created an urgent need for automatic and interpretable models that can evaluate the image-text alignment in long prompt scenarios. However, the existing T2I alignment benchmarks predominantly focus on short prompt scenarios and onl

Cited by 0SourcePDFScholar
2026

TuningIQA: Fine-Grained Blind Image Quality Assessment for Livestreaming Camera Tuning

AAAI 2026technical

Livestreaming has become increasingly prevalent in modern visual communication, where automatic camera quality tuning is essential for delivering superior user Quality of Experience (QoE). Such tuning requires accurate blind image quality assessment (BIQA) to guide parameter optimization decisions.

Cited by 0SourcePDFScholar