RL-ScanIQA: Reinforcement-Learned Scanpaths for Blind 360°Image Quality Assessment

• URL: http://arxiv.org/abs/2603.14297v1
• Date: Sun, 15 Mar 2026 09:21:07 GMT
• Title: RL-ScanIQA: Reinforcement-Learned Scanpaths for Blind 360°Image Quality Assessment
• Abstract summary: Blind 360image quality assessment aims to predict perceptual quality for panoramic images without a pristine reference.<n>We propose RL-ScanIQA, a reinforcement-learned framework for blind 360IQA.<n>Experiments on three benchmarks show that RL-ScanIQA achieves superior in-dataset performance and cross-dataset generalization.
• Score: 30.321209907137856
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Blind 360°image quality assessment (IQA) aims to predict perceptual quality for panoramic images without a pristine reference. Unlike conventional planar images, 360°content in immersive environments restricts viewers to a limited viewport at any moment, making viewing behaviors critical to quality perception. Although existing scanpath-based approaches have attempted to model viewing behaviors by approximating the human view-then-rate paradigm, they treat scanpath generation and quality assessment as separate steps, preventing end-to-end optimization and task-aligned exploration. To address this limitation, we propose RL-ScanIQA, a reinforcement-learned framework for blind 360°IQA. RL-ScanIQA optimize a PPO-trained scanpath policy and a quality assessor, where the policy receives quality-driven feedback to learn task-relevant viewing strategies. To improve training stability and prevent mode collapse, we design multi-level rewards, including scanpath diversity and equator-biased priors. We further boost cross-dataset robustness using distortion-space augmentation together with rank-consistent losses that preserve intra-image and inter-image quality orderings. Extensive experiments on three benchmarks show that RL-ScanIQA achieves superior in-dataset performance and cross-dataset generalization. Codes are available at https://github.com/wangyuji1/RLScanIQA.git.

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