Reproduction of the paper "Local Laplacian filters: edge-aware image processing with a Laplacian pyramid" for the course Advanced Digital Image Processing at TU Delft
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Updated
Oct 8, 2021 - Python
Reproduction of the paper "Local Laplacian filters: edge-aware image processing with a Laplacian pyramid" for the course Advanced Digital Image Processing at TU Delft
RefNet is a 2M-parameter edge-aware transformer for structured introspection and reflective evaluation within Structured Reflective Cognitive Architecture (SRCA/SRAI) systems. It predicts cognitive metrics (valence, self-model drift, thought quality) and recommends introspective actions (consolidate, recall, reframe, evaluate_alignment)
GPU-accelerated iterative bilateral solver for edge-aware refinement.
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