DATASET FOR COMPLEXITY ANALYSIS OF VVC ENCODING AND DECODING
While the next generation video compression standard, Versatile Video Coding (VVC), provides a superior compressing efficiency, its computational complexity dramatically increases. This dataset provides a thoroug analisis on complexity of both encoder and decoder of VVC Test Model 6.0. Encoding and decoding operations have been performed for six video sequences of 720p, 1080p, and 2160p resolutions, and under Low-Delay (LD), Random-Access (RA), and All-Intra (AI) conditions (a total of 320 encoding/decoding operations). All operations were analyzed with Intel VTune 2019 and results of these analysis are collected and reported in this dataset, in csv files. Moreover complexity of encoding and decoding operation have been categorized into six coding/decoding classes and details of each test video sequence have been reported through 4 tables in Tabulated_Report.docx.
This dataset serves as suplementary material for our paper:
Farhad Pakdaman, Mohammad Ali Adelimanesh, Moncef Gabbouj, Mahmoud Reza Hashemi, "Complexity Analysis Of Next-Generation VVC Encoding and Decoding", IEEE International Conference on Image Processing (ICIP), 2020.
This repository includes two sub-folders:
1- VTune_CSV_reports, contains csv reports of VTune for encoding and decoding of 6 sequences using HM 16 and VTM 6. Sub-folders contain reports for LD, RA, and AI configurations, and QP values of 22, 27, 32, and 37. Please refere to VTune documentation for more details on the report format.
2- Encoded_files contains bitstream outputs for all video sequences and all coding conditions.
Moreover, a tabulated report of complexity is extracted from the dataset and is provided here in Tabulated_report.docx.
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