A Survey of Image Quality Evaluation Metrics for Text-to-Image Generation

The survey traces the evolution of image‑quality evaluation for text‑to‑image generation—from early handcrafted edge and color cues, through GAN‑era similarity scores such as IS, FID and KID, to modern perceptual and CLIP‑based metrics like LPIPS, CLIPScore, TRIQ, IQT and human‑preference models—highlighting a shift toward semantic, aesthetic, and text‑image alignment measures and forecasting domain‑specific metrics for future diffusion models.

GaNGenerative Modelsevaluation metrics

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A Survey of Image Quality Evaluation Metrics for Text-to-Image Generation

Alibaba Cloud Developer

Feb 21, 2019 · Artificial Intelligence

How Alibaba Uses AI to Automatically Find High‑Quality Buyer Photos on Taobao

This article explains how Alibaba’s algorithm team tackles the massive challenge of extracting high‑quality buyer‑generated images from Taobao by combining statistical features, GBDT classification, deep CNN visual assessment, aesthetic scoring, and dirty‑data filters to improve content moderation efficiency.

AIUGCcontent moderation

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How Alibaba Uses AI to Automatically Find High‑Quality Buyer Photos on Taobao

Xianyu Technology

Jun 30, 2018 · Artificial Intelligence

No-Reference Image Sharpness Assessment Based on Strong Edge Validity Statistics

The paper proposes a no‑reference image sharpness metric that computes strong‑edge validity statistics—ratio of maximum directional gradient sum to squared strong‑edge count—across image blocks, classifies them into grades, and effectively handles defocus and motion blur for applications such as video thumbnail selection.

No-Referencecomputer visionedge statistics

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No-Reference Image Sharpness Assessment Based on Strong Edge Validity Statistics