Recent Advances in Face Image Super-Resolution: Characteristics, Datasets, Models, and Loss Functions

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What does 𝐗 represent in the context of the text?

Ground truth image

What is the purpose of PSNR in image restoration?

Full-reference objective quality assessment

Why is the 𝑙2 loss prevalent for image/video restoration tasks?

Highly correlated to PSNR

Where can the source code for SSIM be found?

<a href="https://github.com/utlive/ssim">https://github.com/utlive/ssim</a> Signup and view all the answers

Why are task-specific evaluation metrics needed for tasks like RSISR?

Goals and characteristics of RSISR need to be considered Signup and view all the answers

What does 𝐗̂ represent in the context of the text?

Super-resolved image Signup and view all the answers

Where can the source code for LPIPS be accessed?

<a href="https://github.com/richzhang/PerceptualSimilarity">https://github.com/richzhang/PerceptualSimilarity</a> Signup and view all the answers

What are some common targets in super-resolution tasks like RSISR?

Smoothness preserving, detail enhancing, sharpening for edges Signup and view all the answers

Why is an evaluation criterion desired that covers region-differentiated goals in super-resolution tasks?

To cover diverse goals like smoothness, detail, sharpening Signup and view all the answers

What does PSNR stand for?

Peak signal-to-noise ratio Signup and view all the answers

Why is developing an automatic model for measuring visual quality accurately a challenge?

No HR images for reference in practical applications Signup and view all the answers

What is the main goal of super-resolution tasks like RSISR?

Better human visual perception Signup and view all the answers

What is the main focus of the review conducted by Nguyen et al.?

SR approaches for biometrics such as iris, face, fingerprint, and gait Signup and view all the answers

What is the distinguishing factor between studies on RSISR and conventional image SR techniques?

Characteristics of real-world images Signup and view all the answers

What are the four main contributions of the review on RSISR?

Review studies, present taxonomy, compare algorithms, discuss challenges Signup and view all the answers

Which section briefly introduces the background of RSISR?

Section 2 Signup and view all the answers

In which section are the datasets and assessment metrics for RSISR described?

Section 3 Signup and view all the answers

What does Section 4 of the review focus on?

RSISR technologies and methods by category Signup and view all the answers

What is the main reason for the significant degradation of SR performance on real-world images?

Domain gap between synthetic and realistic data Signup and view all the answers

What has been the focus of some researchers over the past few years in response to the domain gap issue?

Real-world single image SR (RSISR) Signup and view all the answers

Which conferences have organized challenges on RSISR to attract attention and promote the development of RSISR techniques?

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE International Conference on Computer Vision (ICCV), European Conference on Computer Vision (ECCV) Signup and view all the answers

What is one positive trend observed in recent studies on RSISR?

Improvement in SR performance on real-world images Signup and view all the answers

Besides RSISR, what other types of techniques have been overviewed in some works?

Video and image SR techniques Signup and view all the answers

Which authors reviewed the architectures and implementation details of state-of-the-art deep learning-based video SR methods?

Liu et al. Signup and view all the answers

What features are used in the model to estimate the final perceptual score?

Distribution of discrete cosine transform coefficients, distribution of wavelet coefficients, spatial discontinuity property of pixel intensity Signup and view all the answers

What dataset are the three regression forests and linear regression model trained on?

Large-scale dataset of super-resolved images with perceptual scores Signup and view all the answers

What does the term 𝐗̃ in the equation represent?

Super-resolved image generated by a non-blind learning-based method Signup and view all the answers

What is the purpose of the direct bi-𝑙0 -𝑙2 -norm regularization term 𝜂(𝐗, 𝐛) in the equation?

Beneficial to the accurate estimation of blur kernel 𝐛 Signup and view all the answers

How can the estimated blur kernel ̂𝐛 be used in the process?

Combined with non-blind super-resolution methods to produce a high-resolution estimate Signup and view all the answers

What image prior is introduced by Shao et al. to further improve the approach?

𝑙𝛼 -norm-based adaptive heavy-tailed image prior Signup and view all the answers