Abstract:In recent years, Depth-Image-Based-Rendering (DIBR) synthesized views have gained popularity due to their numerous visual media applications. Consequently, the research in their quality assessment (QA) has also gained momentum. In this work, we propose an efficient metric to estimate the perceptual quality of DIBR synthesized views via the extraction of Deep-features. These Deep-features are extracted from a pretrained CNN model. Generally, in DIBR synthesized views, geometric distortions arise near the object… Show more
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