Snis896mp4

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3. SNIS‑896MP4 Architecture

3.1 Overview

Figure 1 illustrates the high‑level pipeline. The encoder receives raw YUV 4:2:0 frames, processes them through a multi‑scale feature extractor (MFE), then quantizes the latent representation with a learned context‑adaptive entropy model (C‑EAM). The resulting bitstream is packaged into MP4 mdat and custom snis boxes that delineate base and enhancement layers. The decoder mirrors the pipeline, progressively reconstructing the frame as more layers become available. snis896mp4

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3.3 Context‑Adaptive Entropy Model (C‑EAM)

C‑EAM predicts a conditional probability distribution for each latent coefficient using a lightweight Pixel‑CNN‑like context. The model shares parameters with the MFE (weight‑tying), yielding zero additional parameters. Entropy coding is performed via Range Asymmetric Numeral Systems (RANS), achieving near‑optimal compression for the learned distribution. SNIS‑896MP4 Architecture 3

File Size: Depending on the compression and resolution, the file usually ranges from 1.5 GB to 6 GB.

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