diffusion 3

[24.08.21 / CVPR 24'] Brush2Prompt: Contextual Prompt Generator for Object Inpainting

https://openaccess.thecvf.com/content/CVPR2024/papers/Chiu_Brush2Prompt_Contextual_Prompt_Generator_for_Object_Inpainting_CVPR_2024_paper.pdfObject inpainting is a task that involves adding objects to real images and seamlessly compositing them. With the recent commercialization of products like Stable Diffusion and Generative Fill, inserting objects into images by using prompts has achieved imp..

[24.08.02 / ICCV23'] Distribution-Aligned Diffusion for Human Mesh Recovery

https://openaccess.thecvf.com/content/ICCV2023/papers/Foo_Distribution-Aligned_Diffusion_for_Human_Mesh_Recovery_ICCV_2023_paper.pdfAbstractRecovering a 3D human mesh from a single RGB image is a challenging task due to depth ambiguity and self-occlusion, resulting in a high degree of uncertainty. Meanwhile, diffusion models have recently seen much success in generating high-quality outputs by p..

[24.07.30 / CVPR24'] DiG-IN: Diffusion Guidance for Investigating Networks - Uncovering Classifier Differences Neuron Visualizations and Visual Counterfactual Explanations

https://openaccess.thecvf.com/content/CVPR2024/papers/Augustin_DiG-IN_Diffusion_Guidance_for_Investigating_Networks_-_Uncovering_Classifier_Differences_CVPR_2024_paper.pdfAbstract While deep learning has led to huge progress in complex image classification tasks like ImageNet, unexpected failure modes, e.g. via spurious features, call into question how reliably these classifiers work in the wild..