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A user shares enthusiasm for "Anatomy," a Claude-based tool that turns one-line machine descriptions into interactive isometric 3D wireframes with WebGL shaders and movable parts, hailing it as "the future of learning."
This paper introduces a new task, reference-guided generated content super-resolution-refinement (RefGC-SR²), which simultaneously recovers high-resolution details and refines generative artifacts using a frequency-aware diffusion transformer model. The method leverages a high-resolution reference image to improve the quality of AI-generated images during post-processing.