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Enhancing Adversarial Training with Prior Knowledge Distillation for Robust Image Compression
Adversarial training has been validated in image compression models as a common method to enhance model robustness.
Universal Learned Image Compression With Low Computational Cost
Recently, learned image compression methods have developed rapidly and exhibited excellent rate-distortion performance when compared to traditional standards, such as JPEG, JPEG2000 and BPG.
Transformations in Learned Image Compression from a Modulation Perspective
In the view of TSM, the existing transformation methods are mathematically reduced to a linear modulation.
Exploring Structural Sparsity in Neural Image Compression
Neural image compression have reached or out-performed traditional methods (such as JPEG, BPG, WebP).
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