Saliency-Aware Video Compression

By H. Hadizadeh, I. Bajić. IEEE Transactions on Image Processing, 2014

311 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/edf3d2f5ad0473698fcdb5dad712734ef1365524

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In Computer Vision and Pattern Recognition

Citations in the corpus

Predicting Human Eye Fixations via an LSTM-Based Saliency Attentive Model (2016, background): “An intensive research effort aimed to emulate such selective visual mechanisms, as computational saliency can be applied to a wide range of applications like image retargeting [2], [3], object recognition [4], video compression [5], tracking [6] and other data-dependent tasks such as image captionin”
Shifting More Attention to Video Salient Object Detection (2019, background): “…the underlying mechanism behind HVS during free-viewing in general and instrumental to a wide range of real-world applications, e.g ., video segmentation [74, 83], video captioning [57], video compression [27, 29], autonomous driving [91], robotic interaction [82], weakly supervised attention [95].”
Gaze Prediction in Dynamic 360° Immersive Videos (2018, background): “Most of the models are based on the bottom-up [10] [2] [14] [23], top-down [25] [13] [8] [22] [29], or hybrid approaches to detect salient regions on images.”
Saliency in VR: How Do People Explore Virtual Environments? (2016, methodology): “Inspired by saliency-aware video compression schemes [19], we test an intuitive approach to saliency-aware compression for omni-directional stereo panoramas.”
DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations (2015, methodology): “This modeling has applications in vision-related tasks such as video compression [8], object and action recognition [9], [10], image retargetting [11] and surveillance systems [12].”
Deep Level Sets for Salient Object Detection (2017, methodology): “Inspired by this biological capability, visual saliency computation is introduced into the field of computer vision for its potential to enhance tasks like image processing [4, 12], image understanding [58, 63], video analysis and compression [13, 45].”