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[IEEE TII 2025] Official Implementation for "VarAD: Lightweight High-Resolution Image Anomaly Detection via Visual Autoregressive Modeling" Resources

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2024年12月12日 · 在 ImageNet 256×256 基准测试中，VAR 显着提高了其 AR 基线，实现了 1.73 的 Fréchet 起始距离 (FID) 和 35.2 的初始分数 (IS)，推理速度快 20 倍（详见第 7 节）。 值得注意的是，VAR超过了扩散变压器 (DiT)——在FID/IS、数据效率、推理速度和可扩展性方面，如稳定扩散3.0和SORA。 VAR 模型 也表现出类似于 LLM 中所见的标度律。 最后，我们展示了VAR在图像修复、外绘和编辑等任务中的零镜头泛化能力。 总之，我们对社区的贡献包括： 一种新的视 …

2025年1月16日 · Comprehensive experiments on four publicly available datasets and a real-world button inspection dataset demonstrate that the proposed VarAD achieves superior HRIAD performance while maintaining lightweight, rendering VarAD a viable solution for HRIAD.