Our approach combines the semantic classification ability of the cross-attention module within the diffusion model with score-based conditional guidance to achieve high-quality image reconstruction and precise identification of discriminative regions. Experimental results have demonstrated that our anomaly ...
Dataset Image Label Example Label Guidance Beam Nucleus CLIP Prompt Weighting CIFAR-100 forest, fox, bed ✔ ✘ ✔ ✘ ✔ CIFAR-10 airplane, bird, ship ✔ ✘ ✘ ✔ ✔ Cal101 anchor, cellphone, pyramid ✔ ✘ ✔ ✘ ✘ Cars Acura_Integra_Type_R_2001, AM_General_Humm...
2.4 Classifier-free guidance 按照Conditional DDPM的采样过程的话,采样得到的结果虽然有很高的多样性,但是得到的结果可能并不能达到很好的真实性,而且结果和语义图之间的关系也可能得不到很好的保持。在之前的文章中提到过,conditional diffusion model采样的质量可以通过加入 $\triangledown_{y_t}log p(x | y_t)...
为了进一步提高语义图像合成中的生成质量和语义可解释性,我们引入了无分类器引导( classifier-free guidance)的采样策略,该策略被公认为采样过程中的无条件模型的核心。我们在三个基准(baseline)数据集上进行的大量实验,证明了提出的方法的有效性,在保真度 (FID) 和多样性 (LPIPS) 方面实现了目前最高水平的效果。 1...
HuggingFace Research Introduces LEDITS: The Next Evolution in Real-Image Editing Leveraging DDPM Inversion and Enhanced Semantic Guidance
2.2.2. Classifier-free guidance (CFG) for semantic image synthesis In this study, a new CFG strategy [52] has been incorporated into the reverse diffusion process to improve conditional integration. This approach calculates the mean predicted noise through linear interpolation between the noise predic...
Cord, “Diffedit: Diffusion-based semantic image editing with mask guidance,” in Proc. the Eleventh Int. Conf. Learning Representations, Kigali, Rwanda, 2023.. Google Scholar [52] B. Wallace, A. Gokul, and N. Naik, “EDICT: Exact diffusion inversion via coupled transformations,” in ...
In this paper, we propose a novel structure-guided diffusion model for image inpainting (namelyStrDiffusion), which reformulates the conventional texture denoising process under the guidance of the structure to derive a simplified denoising objective (Eq.11) for inpainting, while revealing: 1) the ...
1. Given a set of train- ing samples with weakly-annotated scribbles, our aim is to learn a more robust segmentation model. Due to the limited label information of scribbles, there usually lacks sufficient guidance to train an excellent segmentation model. To cir- cumvent this problem, on...
V:guidance mapF:boundary-enhanced feature map 从原始骨干特征到边界感知特征的可区分映射。 SDC:fuse U & V BN-ReLU: concat+convolution 对比:首先明确是有很多种convolution operator存在的 普通卷积VC、中心差分卷积CDC和语义差分卷积SDC 权值* x 权值* dx 权值* Similarity * dx SDC:权值 * Similarity *...