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Defocus blur detection based on transformer and complementary residual learning
Defocus blur detection (DBD), a technique for detecting defocus or in-focus pixels in a single image, has been widely used in various fields....
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Defocus blur detection via adaptive cross-level feature fusion and refinement
Convolutional neural networks have achieved competitive performance in defocus blur detection (DBD). However, due to the different receptive fields...
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Defocus Blur detection via transformer encoder and edge guidance
Defocus blur detection (DBD) aims to separate blurred and unblurred regions for a given image. Benefiting from the powerful extraction capabilities...
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Defocus blur detection using novel local directional mean patterns (LDMP) and segmentation via KNN matting
Detection and segmentation of defocus blur is a challenging task in digital imaging applications as the blurry images comprise of blur and sharp...
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United Defocus Blur Detection and Deblurring via Adversarial Promoting Learning
Understanding blur from a single defocused image contains two tasks of defocus detection and deblurring. This paper makes the earliest effort to...
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A model-independent method for local blur estimation and its application to edge detection
Knowledge is hidden in images in form of objects, structures, patterns and their relationships, which are acquired through devices associated with...
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Single image defocus map estimation through patch blurriness classification and its applications
Depth information is useful in many image processing applications. However, since taking a picture is a process of projection of a 3D scene onto a 2D...
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Leveraging Blur Information for Plenoptic Camera Calibration
This paper presents a novel calibration algorithm for plenoptic cameras, especially the multi-focus configuration, where several types of...
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Image enhancement and blur pixel identification with optimization-enabled deep learning for image restoration
Image enhancement is the process of enhancing specific aspects of an image, such as its borders or contrast. The procedure of restoring a destroyed...
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A zoom tracking algorithm based on defocus difference
The image clarity evaluation function was commonly used by the autofocus algorithm to evaluate the clarity of the image. And autofocus algorithms...
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Defocus Blur Detection via Depth Distillation
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...
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CNN-SVM with Data Augmentation for Robust Blur Detection of Digital Breast Tomosynthesis Images
Digital breast tomosynthesis (DBT) is a method that extends digital mammography by capturing pictures of the breast from various angles of the x-ray...
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Detection of local motion blurred/non-blurred regions in an image
Motion blur of an image is a common phenomenon that occurs while taking a photograph due to the relative movement of the object and an image...
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Dual-Memory Feature Aggregation for Video Object Detection
Recent studies on video object detection have shown the advantages of aggregating features across frames to capture temporal information, which can...
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Rethinking the Defocus Blur Detection Problem and a Real-Time Deep DBD Model
Defocus blur detection (DBD) is a classical low level vision task. It has recently attracted attention focusing on designing complex convolutional...
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A single defocused image depth recovery with superpixel segmentation
Most of the depth restoration algorithms are complicated for a single defocused image, the restoration effect is poor on the image edges, complex...
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Deblur and deep depth from single defocus image
In this paper, we tackle depth estimation and blur removal from a single out-of-focus image. Previously, depth is estimated, and blurred is removed...
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RoICLIP: Text-Enhanced UAV-Based Video Object Detection
In recent years, Unmanned Aerial Vehicles (UAV)-based video object detection algorithms have attracted a lot of attention due to their widespread...
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Video Object Detection with MeanShift Tracking
Video object detection, a basic task in the computer vision, is rapidly evolving and widely used in various real-world applications. Recently, with...
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Encoding laparoscopic image to words using vision transformer for distortion classification and ranking in laparoscopic videos
Laparoscopic videos are tools used by surgeons to insert narrow tubes into the abdomen and keep the skin without large incisions. The videos captured...
