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Found 5 papers, 2 papers with code
Exploring Effective Priors and Efficient Models for Weakly-Supervised Change Detection
Specifically, change missing refer to the situation that the WSCD model fails to predict any changed pixels, even though the image-level label indicates changed, and vice versa for change fabricating.
Fast QTMT Partition for VVC Intra Coding Using U-Net Framework
Experimental results demonstrate that our solution outperforms the state-of-the-art works with a complexity reduction of 44. 74% to 68. 76% and a BD-BR increase of 0. 60% to 2. 33%.
Thousand to One: Semantic Prior Modeling for Conceptual Coding
To this end, we propose a novel end-to-end semantic prior modeling-based conceptual coding scheme towards extremely low bitrate image compression, which leverages semantic-wise deep representations as a unified prior for entropy estimation and texture synthesis.
Conceptual Compression via Deep Structure and Texture Synthesis
To this end, we propose a novel conceptual compression framework that encodes visual data into compact structure and texture representations, then decodes in a deep synthesis fashion, aiming to achieve better visual reconstruction quality, flexible content manipulation, and potential support for various vision tasks.
Image and Video Compression with Neural Networks: A Review
Deep convolution neural network (CNN) which makes the neural network resurge in recent years and has achieved great success in both artificial intelligent and signal processing fields, also provides a novel and promising solution for image and video compression.
