We propose a learning-based image compression method that achieves any arbitrary input bitrate via user-guided bit allocation to preferred regions.
We propose a learning-based image compression method that achieves any arbitrary input bitrate via user-guided bit allocation to preferred regions.
Traditional image compression standards, like JPEG [23],. JPEG2000 [19], and HEVC [17] rely on hand-crafted mod- ules involving discrete cosine transforms ...
Introduced here are techniques/technologies that enable user-guided variable-rate image compression. The user provides an image to be compressed and a ...
We propose a learning-based image compression method that achieves any arbitrary input bitrate via user-guided bit allocation to preferred regions.
Mar 16, 2023 · Variable-rate mechanism has improved the flexibility and efficiency of learning-based image compression that trains multiple models for ...
A summary of image compression papers & code. Variable Rate Image Compression with Recurrent Neural Networks.
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Oct 1, 2024 · This paper proposes to exploit a differentiable quantizer designed around a parametric sum of hyperbolic tangents, called STanH, that relaxes the step-wise ...
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This paper introduces a Spatial Importance Guided Variable-rate Image Compression (SigVIC), in which a spatial gating unit (SGU) is designed for adaptively ...
May 24, 2024 · We study the design of deep architectures for lossy image compression. We present two architectural recipes in the context of multi-stage ...