Image inpainting: A review
Although image inpainting, or the art of repairing the old and deteriorated images, has been
around for many years, it has recently gained even more popularity, because of the recent …
around for many years, it has recently gained even more popularity, because of the recent …
CitySim: a drone-based vehicle trajectory dataset for safety-oriented research and digital twins
O Zheng, M Abdel-Aty, L Yue… - Transportation …, 2024 - journals.sagepub.com
The development of safety-oriented research and applications requires fine-grain vehicle
trajectories that not only have high accuracy, but also capture substantial safety-critical …
trajectories that not only have high accuracy, but also capture substantial safety-critical …
Advancing image understanding in poor visibility environments: A collective benchmark study
Existing enhancement methods are empirically expected to help the high-level end
computer vision task: however, that is observed to not always be the case in practice. We …
computer vision task: however, that is observed to not always be the case in practice. We …
IID-Net: Image inpainting detection network via neural architecture search and attention
Deep learning (DL) has demonstrated its powerful capabilities in the field of image
inpainting, which could produce visually plausible results. Meanwhile, the malicious use of …
inpainting, which could produce visually plausible results. Meanwhile, the malicious use of …
A flexible deep CNN framework for image restoration
Image restoration is a long-standing problem in image processing and low-level computer
vision. Recently, discriminative convolutional neural network (CNN)-based approaches …
vision. Recently, discriminative convolutional neural network (CNN)-based approaches …
A review of advances in image inpainting research
H Li, L Hu, J Liu, J Zhang, T Ma - The Imaging Science Journal, 2024 - Taylor & Francis
The aim of image inpainting is to fill in damaged areas according to certain rules based on
information about the adjacent positions of missing areas and the overall structure of the …
information about the adjacent positions of missing areas and the overall structure of the …
Deep plastic surgery: Robust and controllable image editing with human-drawn sketches
Sketch-based image editing aims to synthesize and modify photos based on the structural
information provided by the human-drawn sketches. Since sketches are difficult to collect …
information provided by the human-drawn sketches. Since sketches are difficult to collect …
A benchmark for sparse coding: When group sparsity meets rank minimization
Sparse coding has achieved a great success in various image processing tasks. However, a
benchmark to measure the sparsity of image patch/group is missing since sparse coding is …
benchmark to measure the sparsity of image patch/group is missing since sparse coding is …
Deep generative model for image inpainting with local binary pattern learning and spatial attention
Deep learning (DL) has demonstrated its powerful capabilities in the field of image
inpainting. The DL-based image inpainting approaches can produce visually plausible …
inpainting. The DL-based image inpainting approaches can produce visually plausible …
Jpgnet: Joint predictive filtering and generative network for image inpainting
Image inpainting aims to restore the missing regions of corrupted images and make the
recovery result identical to the originally complete image, which is different from the common …
recovery result identical to the originally complete image, which is different from the common …