Explicit visual prompting for low-level structure segmentations
We consider the generic problem of detecting low-level structures in images, which includes
segmenting the manipulated parts, identifying out-of-focus pixels, separating shadow …
segmenting the manipulated parts, identifying out-of-focus pixels, separating shadow …
Edge-based defocus blur estimation with adaptive scale selection
Objects that do not lie at the focal distance of a digital camera generate defocused regions in
the captured image. This paper presents a new edge-based method for spatially varying …
the captured image. This paper presents a new edge-based method for spatially varying …
Enhancing diversity of defocus blur detectors via cross-ensemble network
Defocus blur detection (DBD) is a fundamental yet challenging topic, since the
homogeneous region is obscure and the transition from the focused area to the unfocused …
homogeneous region is obscure and the transition from the focused area to the unfocused …
Explicit visual prompting for universal foreground segmentations
Foreground segmentation is a fundamental problem in computer vision, which includes
salient object detection, forgery detection, defocus blur detection, shadow detection, and …
salient object detection, forgery detection, defocus blur detection, shadow detection, and …
Defocus blur detection via depth distillation
Abstract Defocus Blur Detection (DBD) aims to separate in-focus and out-of-focus regions
from a single image pixel-wisely. This task has been paid much attention since bokeh effects …
from a single image pixel-wisely. This task has been paid much attention since bokeh effects …
Deep multi-scale feature learning for defocus blur estimation
This paper presents an edge-based defocus blur estimation method from a single defocused
image. We first distinguish edges that lie at depth discontinuities (called depth edges, for …
image. We first distinguish edges that lie at depth discontinuities (called depth edges, for …
Image retargeting quality assessment based on saliency-driven classification
Z Tang, J Yao - Signal Processing: Image Communication, 2022 - Elsevier
The overall geometric distortions of the visually prominent contents in resized images are
sensitive to human perception. But the existing image retargeting quality assessment (IRQA) …
sensitive to human perception. But the existing image retargeting quality assessment (IRQA) …
Noise-immune image blur detection via sequency spectrum truncation
X Liang, X Wang, L Lyu, Y Han, J Zheng, W Guo… - Complex & Intelligent …, 2022 - Springer
Blur detection is aimed to differentiate the blurry and sharp regions from a given image. This
task has attracted much attention in recent years due to its importance in computer vision …
task has attracted much attention in recent years due to its importance in computer vision …
Multi-operator image retargeting with preserving aspect ratio of important contents
Q Zhang, Z Tang, H Jiang, K Chang - Pacific Rim Conference on …, 2017 - Springer
Content-aware image retargeting can preserve the quality of visually important objects
during image resizing. However, some previous approaches fail to provide desired results …
during image resizing. However, some previous approaches fail to provide desired results …