Video Quality Assessment Datasets

Below is a summary list of the datasets available with a short description.

Please click on the title or 'more' to learn more about the dataset, work and download links.

Light-Field Video Dataset with a Plenoptic Video Camera

K. Javidi and M. G. Martini, A Light-Field Video Dataset of Scenes with Moving Objects Captured with a Plenoptic Video Camera, Electronics, vol. 13, no. 11,  June 2024. 

The light field dataset contains six distinctive original video contents with 336 distorted light field videos.

Turntable-Based Light Field Dataset

K. Javidi, M.G. Martini, and P. A. Kara, "KULF-TT53: a display-specific turntable-based light field dataset for subjective quality assessment", Electronics, vol. 12, no. 23, Dec 2023.  

The dataset contains seven light field image contents  captured via DSLR camera and objects on turntable.

mULTI-SCREEN Dataset

N. Barman, Y. Reznik and M. G. Martini, "A Subjective Dataset for Multi-Screen Video Streaming Applications," 2023 15th International Conference on Quality of Multimedia Experience (QoMEX), Ghent, Belgium, 2023, pp. 270-275, doi: 10.1109/QoMEX58391.2023.10178645.

The dataset provides subjective ratings obtained for various HEVC-encoded video sequences of multiple resolution-bitrate pairs viewed on three different devices: Mobile, Tablet and TV. More

User Generated HDR Gaming Video Streaming Dataset

N. Barman and M. G. Martini, "User Generated HDR Gaming Video Streaming: Dataset, Codec Comparison, and Challenges," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 32, no. 3, pp. 1236-1249, March 2022, doi: 10.1109/TCSVT.2021.3077384.

The dataset consists of eighteen 10-bit UHD-HDR gaming videos and encoded video sequences using four different codecs, together with their objective evaluation…More

LCEVC LIVE GAMING VIDEO STREAMING DATASET

N. Barman, S. Schmidt, S. Zadtootaghaj, & M. G. Martini (2022). Codec Compression Efficiency Evaluation of MPEG-5 part 2 (LCEVC) using Objective and Subjective Quality Assessment. ArXiv, abs/2204.05580.

This dataset provides the subjective and objective assessment results for the latest MPEG-5 Part 2 codec, commonly known as LOW COMPLEXITY ENHANCED VIDEO CODING considering a live gaming video streaming scenario. More

A high-angular-resolution turntable data-set for experiments on light field visualization quality

Tamboli, R. R., Reddy, M. S., Kara, P. A., Martini, M. G., Channappayya, S. S., & Jana, S. (2018, May). A high-angular-resolution turntable data-set for experiments on light field visualization quality. In 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX). 

High-angular-resolution dataset created using a turntable arrangement. Seven distinct objects, positioned on an automated…More 

GamingVideoSET: dataset for gaming video streaming applications

N. Barman, S. Zadtootaghaj, S. Schmidt, M. G. Martini and S. Möller, "GamingVideoSET: A Dataset for Gaming Video Streaming Applications," 2018 16th Annual Workshop on Network and Systems Support for Games (NetGames), Amsterdam, Netherlands, 2018, pp. 1-6, doi: 10.1109/NetGames.2018.8463362.

The dataset, designed for the research community working on gaming video quality assessment, consists of twenty-four uncompressed raw gaming videos of…More

KUGVD – Kingston University Gaming Video Dataset

N. Barman, E. Jammeh, S. A.  Ghorashi, M. G.  Martini, "No-reference video quality estimation based on machine learning for passive gaming video streaming applications",  IEEE Access, vol. 7, 2019, pp. 74511-74527. 

The dataset is available for non-commercial purposes. You can download the dataset here For further information, see the associated paper. Please cite the paper if you use…More 

EQSST (Estimation of Quality Scores from Subjective Tests)

S. Pezzulli, M. G. Martini and N. Barman, "Estimation of Quality Scores From Subjective Tests-Beyond Subjects’ MOS," in IEEE Transactions on Multimedia, vol. 23, 20pp. 2505-2519, 2021, doi: 10.1109/TMM.2020.3013349.

The dataset contains per-subject assessment results for the content in GamingVideoSet. Beyond the dataset, the SAS code used in the paper is also provided. The…More 

Labeling effect HD vs. UHD (results only)

Please refer to the following publications to learn more about this work:

Kara, P. A., Robitza, W., Raake, A., & Martini, M. G. (2017, May). The label knows better: the impact of labeling effects on perceived quality of HD and UHD video streaming. In 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX) (pp. 1-6). IEEE.

Kara, P. A., Robitza, W., Pinter, N., Martini, M. G., Raake, A., & Simon, A. (2019). Comparison of HD and UHD video quality with and without the influence of the labeling effect. Quality and User Experience, 4(1), 1-29.

Link to results dataset

3D video over LTE dataset

Nasralla, M. M., Hewage, C. T., & Martini, M. G. (2014, July). Subjective and objective evaluation and packet loss modeling for 3D video transmission over LTE networks. In 2014 International Conference on Telecommunications and Multimedia (TEMU) (pp. 254-259). IEEE.

3D video quality dataset (packet losses)

Hewage, C. T., Martini, M. G., Brandas, M., & De Silva, D. V. S. (2013, June). A study on the perceived quality of 3D video subject to packet losses. In 2013 IEEE International Conference on Communications Workshops (ICC) (pp. 662-666). IEEE.