Token-Wise Attention-Guided Semantic Quality Assessment for Compressed Visual Features

Mon, 29 Jun 2026 00:00:00 +0000

本文针对协作与分布式智能系统中压缩中间特征的语义质量评估问题，提出了一种基于Token级注意力引导的评估方法。该方法利用原始与重建Token之间的内在对应关系，在Token层面进行质量度量，以减少跨Token干扰；同时通过注意力机制区分不同Token对下游任务的重要性，从而更准确地反映压缩特征的语义效用。实验表明，该方法在多种特征编解码器上均优于传统相似性度量，具有良好的鲁棒性。

Vquala 2025 challenge on image super-resolution generated content quality assessment: Methods and results

Sun, 19 Oct 2025 00:00:00 +0000

This paper presents the ISRGC-Q Challenge, built upon the Image Super-Resolution Generated Content Quality Assessment (ISRGen-QA) dataset, and organized as part of the Visual Quality Assessment (VQualA) Competition at the ICCV 2025 Workshops. Unlike existing Super-Resolution Image Quality Assessment (SR-IQA) datasets, ISRGen-QA places a greater emphasis on SR images generated by the latest generative approaches, including Generative Adversarial Networks (GANs) and diffusion models. The primary goal of this challenge is to analyze the unique artifacts introduced by modern super-resolution techniques and to evaluate their perceptual quality effectively. A total of 108 participants registered for the challenge, with 4 teams submitting valid solutions and fact sheets for the final testing phase. These submissions demonstrated state-of-the-art (SOTA) performance on the ISRGen-QA dataset. The …

Hadi Amirpour | ViLab

Token-Wise Attention-Guided Semantic Quality Assessment for Compressed Visual Features

Vquala 2025 challenge on image super-resolution generated content quality assessment: Methods and results