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Depth aware image compression with multi-reference dynamic entropy model
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DOI：10.1016/j.neucom.2026.132971.png)
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Abstract
En 中文
• Investigates the significance of differentiated feature processing according to network depth in the encoder-decoder architecture. • Establishes neighborhood dependencies through adaptive soft thresholding attention and captures complementary features via multi-context integration. • Constructs an entropy model using a depth-aware adaptive framework and multi-reference dynamic entropy modeling to enhance pixel prediction.
Keywords:
Feature processing
Attention mechanism
Entropy modeling
Image compression
Multi-context integration
Journal
IF:
6.5
Papers:
2.5W
Citations:
6.5W
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