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Found 5 papers, 2 papers with code
KonX: Cross-Resolution Image Quality Assessment
Through KonX, we provide empirical evidence of label shifts caused by changes in the presentation resolution.
Going the Extra Mile in Face Image Quality Assessment: A Novel Database and Model
An accurate computational model for image quality assessment (IQA) benefits many vision applications, such as image filtering, image processing, and image generation.
Exploring and Evaluating Image Restoration Potential in Dynamic Scenes
In this paper, to better study an image's potential value that can be explored for restoration, we propose a novel concept, referring to image restoration potential (IRP).
Learning Depth via Leveraging Semantics: Self-supervised Monocular Depth Estimation with Both Implicit and Explicit Semantic Guidance
While the mappings between image and pixel-wise depth are well-studied in current methods, the correlation between image, depth and scene semantics, however, is less considered.
Blindly Assess Image Quality in the Wild Guided by a Self-Adaptive Hyper Network
The vast majority of prior BIQA methods focus on how to predict synthetic image quality, but fail when applied to real-world distorted images.
Ranked #5 on
No-Reference Image Quality Assessment
on TID2013
Blind Image Quality Assessment
No-Reference Image Quality Assessment
+1
