Class-aware adversarial transformers for medical image segmentation
Transformers have made remarkable progress towards modeling long-range dependencies
within the medical image analysis domain. However, current transformer-based models …
within the medical image analysis domain. However, current transformer-based models …
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 …
Bridging global context interactions for high-fidelity image completion
Bridging global context interactions correctly is important for high-fidelity image completion
with large masks. Previous methods attempting this via deep or large receptive field (RF) …
with large masks. Previous methods attempting this via deep or large receptive field (RF) …
Keys to better image inpainting: Structure and texture go hand in hand
Deep image inpainting has made impressive progress with recent advances in image
generation and processing algorithms. We claim that the performance of inpainting …
generation and processing algorithms. We claim that the performance of inpainting …
Image inpainting with cascaded modulation gan and object-aware training
Recent image inpainting methods have made great progress but often struggle to generate
plausible image structures when dealing with large holes in complex images. This is …
plausible image structures when dealing with large holes in complex images. This is …
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 …
Sketchedit: Mask-free local image manipulation with partial sketches
Sketch-based image manipulation is an interactive image editing task to modify an image
based on input sketches from users. Existing methods typically convert this task into a …
based on input sketches from users. Existing methods typically convert this task into a …
Transinpaint: Transformer-based image inpainting with context adaptation
P Shamsolmoali, M Zareapoor… - Proceedings of the …, 2023 - openaccess.thecvf.com
Image inpainting aims to generate realistic content for missing regions of an image. Existing
methods often struggle to produce visually coherent content for missing regions of an image …
methods often struggle to produce visually coherent content for missing regions of an image …
Coordfill: Efficient high-resolution image inpainting via parameterized coordinate querying
Image inpainting aims to fill the missing hole of the input. It is hard to solve this task
efficiently when facing high-resolution images due to two reasons:(1) Large reception field …
efficiently when facing high-resolution images due to two reasons:(1) Large reception field …
High-fidelity image inpainting with GAN inversion
Image inpainting seeks a semantically consistent way to recover the corrupted image in the
light of its unmasked content. Previous approaches usually reuse the well-trained GAN as …
light of its unmasked content. Previous approaches usually reuse the well-trained GAN as …