Diverse inpainting and editing with gan inversion
Recent inversion methods have shown that real images can be inverted into StyleGAN's
latent space and numerous edits can be achieved on those images thanks to the …
latent space and numerous edits can be achieved on those images thanks to the …
Inst-inpaint: Instructing to remove objects with diffusion models
Image inpainting task refers to erasing unwanted pixels from images and filling them in a
semantically consistent and realistic way. Traditionally, the pixels that are wished to be …
semantically consistent and realistic way. Traditionally, the pixels that are wished to be …
Deficiency-aware masked transformer for video inpainting
Recent video inpainting methods have made remarkable progress by utilizing explicit
guidance, such as optical flow, to propagate cross-frame pixels. However, there are cases …
guidance, such as optical flow, to propagate cross-frame pixels. However, there are cases …
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 …
An Improved Face Image Restoration Method Based on Denoising Diffusion Probabilistic Models
Y Pang, J Mao, L He, H Lin, Z Qiang - IEEE Access, 2024 - ieeexplore.ieee.org
Image restoration is a crucial task in computer vision, aiming to fill in missing areas within an
image to restore its integrity. Traditional methods fall short when dealing with intricate facial …
image to restore its integrity. Traditional methods fall short when dealing with intricate facial …
Flow-guided diffusion for video inpainting
Video inpainting has been challenged by complex scenarios like large movements and low-
light conditions. Current methods, including emerging diffusion models, face limitations in …
light conditions. Current methods, including emerging diffusion models, face limitations in …
Magic: Multi-modality guided image completion
Vanilla image completion approaches exhibit sensitivity to large missing regions, attributed
to the limited availability of reference information for plausible generation. To mitigate this …
to the limited availability of reference information for plausible generation. To mitigate this …
Dynamic context-driven progressive image inpainting with auxiliary generative units
Z Wang, K Li, J Peng - The Visual Computer, 2024 - Springer
Image inpainting aims to restore missing or damaged regions of an image with plausible
visual content. Most existing methods always face challenges when dealing with large hole …
visual content. Most existing methods always face challenges when dealing with large hole …
[HTML][HTML] Improved medical image inpainting using automatic multi-task learning driven deep learning approach
PL Rakibe, PD Patil - e-Prime-Advances in Electrical Engineering …, 2024 - Elsevier
Distorted medical images can drastically reduce diagnosis accuracy using computer-aided
diagnostic (CAD) systems. The objective of medical image classification is to improve …
diagnostic (CAD) systems. The objective of medical image classification is to improve …
SwapInpaint2: Towards high structural consistency in identity-guided inpainting via background-preserving GAN inversion
H Li, Y Zhang, W Wang, S Zhang, S Zhang - Pattern Recognition, 2025 - Elsevier
In this work, we propose SwapInpaint2 to enhance the naturalness of identity-guided face
inpainting. The previous version, SwapInpaint, relied on a generic inpainting model for …
inpainting. The previous version, SwapInpaint, relied on a generic inpainting model for …