… • We propose a multiple-solution image inpainting method based on hierarchical VQ-VAE.
The method has two distinctions from previous multiple-solution methods: first, the model …

… We turn to describe how to perform visual prompting using Image Inpainting models. In
Section 3.1, we describe our proposed inpainting model, which is a combination of MAE and VQ…

… Recently, based on the similar quantization mechanism with VQ-VAE… inpainted images,
there are two different types of definition for image inpainting task: deterministic image inpainting …

… Generating diverse structure for image inpainting with hierarchical vq-vae. In Proceedings
of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 10775–…

… The hyperparameters used for training the hierarchical VQ-VAE … We train the hierarchical
VQ-VAE and the texture generator on … Training the hierarchical VQ-VAE takes roughly 8 hours. …

… , we propose an image inpainting method based on a hierarchical VQ-VAE with a vector …
the hierarchical VQVAE inpainting module with ground truth images are image generation and …

… Thus, to further reduce (H, W) to (H/2, W/2) but preserve the reconstruction quality, VQVAE
requires the codebook of size K4. However, VQ-VAE with a large codebook is inefficient due …

… The fundamental difference between a VAE and Vector Quantized-Variational AutoEncoder
(VQ-VAE) is that VAE learns a continuous latent representation, while VQVAE learns a …

… The reason for using all vectors instead of selecting through the semantic selector like in
VQ-VAE is that we expect the transformer to model the relationship with the whole QSVM and …

… Image inpainting refers to the restoration of an image with missing regions in a way that is not
detectable by the observer. The inpainting … In this work, we focus on learning-based image …