Image Quality Assessment
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Benchmarks
Most implemented
Conditional Image Synthesis With Auxiliary Classifier GANs
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
NIMA: Neural Image Assessment
SER-FIQ: Unsupervised Estimation of Face Image Quality Based on Stochastic Embedding Robustness
PyTorch Image Quality: Metrics for Image Quality Assessment
Papers
Rate-distortion optimization for full-reference image quality metrics via stochastic Hessian estimates
Block-based video codecs select coding parameters based on the input by optimizing a rate-distortion trade-off. The conventional distortion choice, the sum of squared errors (SSE), simplifies parameter selection: the SSE…
Image Quality AssessmentFoMo: Forking Moment in Generative Trajectory as a Perceptual Distance
Reference-based image quality assessment (IQA) metrics aim to reflect how humans perceive the perceptual distance between a pair of images. To learn how the human visual system (HVS) operates, recent reference-based IQA …
Image Quality AssessmentToward Vision Language Model-based Assessment of Clinical Quality and Usability of LGE-MR Images for Cardiac Ablation Planning
LGE cardiac MRI is widely used for left atrial fibrosis assessment and ablation planning in atrial fibrillation patients as knowledge of fibrotic tissue regions identified from LGE-MRI is critical for catheter ablation. …
Image Quality AssessmentLatent Ordinal Evidence, Misaligned Outputs: Inference-Time Ordinal Lens Alignment for Multimodal LLMs
Multimodal LLMs apply the language model interface to visual inputs, where ordinal regression tasks such as age estimation, image quality assessment, and disease grading require autoregressive decisions over ordered clas…
Image Quality AssessmentAge EstimationMR-IQA-2: Faithful Image Quality Reflection via Fine-Grained Credit Assignment
Multimodal large language models (MLLMs) have shown strong potential for image quality assessment (IQA) by improving consistency between quality ratings and their underlying reasoning. However, most approaches supervise …
Image Quality AssessmentA Subjective Study on a New Sharpness Informed Class of Metrics
Perceptual loss functions in Deep Neural Network (DNN) deblurring architectures improve the overall quality of restored images. However, few focus on explicitly targeting sharpness in the restorations. We conduct a subje…
Image Quality Assessment