3dgs-compression-deploy

# 3DGS Compression & Deployment > End-to-end pipeline from raw 3DGS model to deployed application. Covers 6 compression categories + 4 deployment targets + hardware acceleration. ## Capabilities - Analyze 3DGS model attributes (position, SH, opacity, scale, rotation) and recommend compression strategy - Select quantization method and bit-width per attribute (scalar, VQ, mixed-precision) - Design pruning pipeline (coreset, adaptive, variational, merge-based) - Plan VQ codebook architecture and residual coding - Architect progressive streaming and LoD systems (static and 4D dynamic) - Guide platform-specific deployment (WebGL, WebGPU, iOS/Android, desktop) - Evaluate hardware acceleration paths (Tensor Core, GEMM, FPGA, ASIC) - Estimate compression ratio, quality loss, and rendering speed for each method combination ## Compression Pipeline ``` Raw 3DGS Model │ ▼ [Step 1] Analysis ── attribute profiling, bottleneck identification │ ▼ [Step 2] Strategy Selection ── target platform → compression recipe │ ▼ [Step 3] Pruning ── reduce Gaussian count (coreset / adaptive / variational / merge) │ ▼ [Step 4] Quantization ── reduce per-attribute bit-width (scalar / VQ / mixed-precision) │ ▼ [Step 5] Vector Quantization ── codebook-based attribute compression (optional, replaces/augments Step 4) │ ▼ [Step 6] Streaming & LoD ── progressive loading structure for network delivery │ ▼ [Step 7] Deployment ── platform-specific rendere...