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Found 4 papers, 1 papers with code
Robustly overfitting latents for flexible neural image compression
We show how our method improves the overall compression performance in terms of the R-D trade-off, compared to its predecessors.
Region-of-Interest Based Neural Video Compression
To the best of our knowledge, our proposals are the first solutions that integrate ROI-based capabilities into neural video compression models.
Invertible DenseNets with Concatenated LipSwish
Furthermore, we propose a learnable weighted concatenation, which not only improves the model performance but also indicates the importance of the concatenated weighted representation.
Invertible DenseNets
We introduce Invertible Dense Networks (i-DenseNets), a more parameter efficient alternative to Residual Flows.
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