Palette: Image-to-image diffusion models
This paper develops a unified framework for image-to-image translation based on
conditional diffusion models and evaluates this framework on four challenging image-to …
conditional diffusion models and evaluates this framework on four challenging image-to …
Sketch-guided text-to-image diffusion models
Text-to-Image models have introduced a remarkable leap in the evolution of machine
learning, demonstrating high-quality synthesis of images from a given text-prompt. However …
learning, demonstrating high-quality synthesis of images from a given text-prompt. However …
Realfill: Reference-driven generation for authentic image completion
Recent advances in generative imagery have brought forth outpainting and inpainting
models that can produce high-quality, plausible image content in unknown regions …
models that can produce high-quality, plausible image content in unknown regions …
A review of image inpainting methods based on deep learning
Image Inpainting is an age-old image processing problem, with people from different eras
attempting to solve it using various methods. Traditional image inpainting algorithms have …
attempting to solve it using various methods. Traditional image inpainting algorithms have …
Catch Missing Details: Image reconstruction with frequency augmented variational autoencoder
The popular VQ-VAE models reconstruct images through learning a discrete codebook but
suffer from a significant issue in the rapid quality degradation of image reconstruction as the …
suffer from a significant issue in the rapid quality degradation of image reconstruction as the …
Deep learning-based image and video inpainting: A survey
Image and video inpainting is a classic problem in computer vision and computer graphics,
aiming to fill in the plausible and realistic content in the missing areas of images and videos …
aiming to fill in the plausible and realistic content in the missing areas of images and videos …
Image super-resolution via latent diffusion: A sampling-space mixture of experts and frequency-augmented decoder approach
The recent use of diffusion prior, enhanced by pre-trained text-image models, has markedly
elevated the performance of image super-resolution (SR). To alleviate the huge …
elevated the performance of image super-resolution (SR). To alleviate the huge …
Blind image inpainting via omni-dimensional gated attention and wavelet queries
Blind image inpainting is a crucial restoration task that does not demand additional mask
information to restore the corrupted regions. Yet, it is a very less explored research area due …
information to restore the corrupted regions. Yet, it is a very less explored research area due …
Semi-supervised video inpainting with cycle consistency constraints
Deep learning-based video inpainting has yielded promising results and gained increasing
attention from researchers. Generally, these methods usually assume that the corrupted …
attention from researchers. Generally, these methods usually assume that the corrupted …
Srinpaintor: When super-resolution meets transformer for image inpainting
Recent image inpainting methods have achieved remarkable improvements by using
generative adversarial networks (GAN). Most of them have been designed to produce …
generative adversarial networks (GAN). Most of them have been designed to produce …