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Found 5 papers, 3 papers with code
Exploring Explainability in Video Action Recognition
To address these, we introduce Video-TCAV, by building on TCAV for Image Classification tasks, which aims to quantify the importance of specific concepts in the decision-making process of Video Action Recognition models.
HIDRO-VQA: High Dynamic Range Oracle for Video Quality Assessment
Our findings demonstrate that self-supervised pre-trained neural networks on SDR content can be further fine-tuned in a self-supervised setting using limited unlabeled HDR videos to achieve state-of-the-art performance on the only publicly available VQA database for HDR content, the LIVE-HDR VQA database.
Study of Subjective and Objective Quality Assessment of Mobile Cloud Gaming Videos
We present the outcomes of a recent large-scale subjective study of Mobile Cloud Gaming Video Quality Assessment (MCG-VQA) on a diverse set of gaming videos.
GAMIVAL: Video Quality Prediction on Mobile Cloud Gaming Content
The mobile cloud gaming industry has been rapidly growing over the last decade.
Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild
To advance research in this field, we propose a Mixture of Experts approach to train two separate encoders to learn high-level content and low-level image quality features in an unsupervised setting.
Ranked #3 on
No-Reference Image Quality Assessment
on CSIQ
