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A diffusion-based shadow caching framework that compresses a vast set of pre-calculated shadow INRs into a single diffusion model that effectively memorizes and reconstructs a dense set of pre-trained lighting conditions on the fly, bypassing the massive storage bloat of independent INRs.
This work presents a systematic compute-platform benchmark of neural 3D reconstruction methods, evaluating NeRF and 3D Gaussian Splatting training and rendering on GPU-enabled computing devices, and place Meta's SAM3D single-image reconstruction on the same axes to quantify its latency and fidelity gap relative to per-...
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