CamFreeDiff: Camera-free Image to Panorama Generation with Diffusion Model

This paper introduces Camera-free Diffusion (CamFreeDiff) model for 360-degree image outpainting from a single camera-free image and text description. This method distinguishes itself from existing strategies, such as MVDiffusion, by eliminating the requirement for predefined camera poses. Instead,...

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Bibliographic Details
Main Authors Yuan, Xiaoding, Tang, Shitao, Li, Kejie, Yuille, Alan, Wang, Peng
Format Journal Article
LanguageEnglish
Published 09.07.2024
Subjects
Computer Science - Computer Vision and Pattern Recognition
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Summary:This paper introduces Camera-free Diffusion (CamFreeDiff) model for 360-degree image outpainting from a single camera-free image and text description. This method distinguishes itself from existing strategies, such as MVDiffusion, by eliminating the requirement for predefined camera poses. Instead, our model incorporates a mechanism for predicting homography directly within the multi-view diffusion framework. The core of our approach is to formulate camera estimation by predicting the homography transformation from the input view to a predefined canonical view. The homography provides point-level correspondences between the input image and targeting panoramic images, allowing connections enforced by correspondence-aware attention in a fully differentiable manner. Qualitative and quantitative experimental results demonstrate our model's strong robustness and generalization ability for 360-degree image outpainting in the challenging context of camera-free inputs.
DOI:10.48550/arxiv.2407.07174