Review of deep learning-based image inpainting techniques
J Yang, NIR Ruhaiyem - IEEE Access, 2024 - ieeexplore.ieee.org
The deep learning-based image inpainting models discussed in this review are critical
image processing techniques for filling in missing or removed regions in static planar …
image processing techniques for filling in missing or removed regions in static planar …
Painterly image harmonization in dual domains
Image harmonization aims to produce visually harmonious composite images by adjusting
the foreground appearance to be compatible with the background. When the composite …
the foreground appearance to be compatible with the background. When the composite …
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 …
EasySpec: Automatic specular reflection detection and suppression from endoscopic images
The outcome of endoscopic tasks can be significantly affected by the presence of specular
reflections. Although numerous methods have been proposed for specular reflection …
reflections. Although numerous methods have been proposed for specular reflection …
Uncertainty-guided appearance-motion association network for out-of-distribution action detection
X Fang, A Easwaran, B Genest - 2024 IEEE 7th International …, 2024 - ieeexplore.ieee.org
Out-of-distribution (OOD) detection targets to detect and reject test samples with semantic
shifts, to prevent models trained on in-distribution (ID) dataset from producing unreliable …
shifts, to prevent models trained on in-distribution (ID) dataset from producing unreliable …
Elimination of defects in mammograms caused by a malfunction of the device matrix
D Tumakov, Z Kayumov, A Zhumaniezov, D Chikrin… - Journal of …, 2022 - mdpi.com
Today, the processing and analysis of mammograms is quite an important field of medical
image processing. Small defects in images can lead to false conclusions. This is especially …
image processing. Small defects in images can lead to false conclusions. This is especially …
Image inpainting for periodic discrete density defects via frequency analysis and an adaptive transformer-GAN network
H Ding, Y Huang, N Chen, J Lu, S Li - Applied Soft Computing, 2024 - Elsevier
Image inpainting based on deep learning has made significant progress in addressing
regular and coherent irregular defects. However, little has been studied on periodic discrete …
regular and coherent irregular defects. However, little has been studied on periodic discrete …
A deep learning image inpainting method based on stationary wavelet transform
The development of deep learning has greatly improved the image inpainting performance
in the past decades. In fact, image inpainting for different tasks usually requires different …
in the past decades. In fact, image inpainting for different tasks usually requires different …
InViT: GAN Inversion-based Vision Transformer for Blind Image Inpainting
Y Du, H Liu, S He, S Chen - IEEE Access, 2024 - ieeexplore.ieee.org
Blind image inpainting, the task of detecting corrupted regions with diverse patterns within
an image and then generating plausible content for the corrupted regions, remains a both …
an image and then generating plausible content for the corrupted regions, remains a both …
Hybrid regularization inspired by total variation and deep denoiser prior for image restoration
H Liang, J Zhang, D Wei, J Zhu - Complex & Intelligent Systems, 2024 - Springer
Image restoration is a fundamental problem in computer vision, with the goal of restoring
high-quality images from degraded low-quality observation images. However, the ill …
high-quality images from degraded low-quality observation images. However, the ill …