AI RESEARCH
Too Vivid to Be Real? Benchmarking and Calibrating Generative Color Fidelity
arXiv CS.CV
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ArXi:2603.10990v1 Announce Type: new Recent advances in text-to-image (T2I) generation have greatly improved visual quality, yet producing images that appear visually authentic to real-world photography remains challenging. This is partly due to biases in existing evaluation paradigms: human ratings and preference-trained metrics often favor visually vivid images with exaggerated saturation and contrast, which make generations often too vivid to be real even when prompted for realistic-style images.