NUS 推出 OmniConsistency：低成本实现图像风格化一致性，挑战 GPT-4o！
近日，新加坡国立大学（NUS）团队发布了一个名为 “OmniConsistency” 的创新项目，旨在以极低的成本复现 OpenAI 的 GPT-4o 模型在图像风格化上的一致性。这项技术不仅解决了当前开源社区在图像风格化和一致性之间的矛盾，还为广大开发者提供了可行的解决方案。近年来，图像风格化的技术不断发展，但在实际应用中，风格与内容一致性之间的平衡一直是个难题。为了增强风格化效果，很多模型往往牺牲了细节和语义的准确性。NUS 的研究团队认识到这个问题，他们的目标是实现风格化效果和
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