Blind image quality prediction by exploiting multi-level deep representations
Blind image quality assessment (BIQA) aims at precisely estimating human perceived image
quality with no access to a reference. Recently, several attempts have been made to …
quality with no access to a reference. Recently, several attempts have been made to …
Face biometric quality assessment via light CNN
In this paper, we proposed a novel biometric quality assessment (BQA) method for face
images and explored its applications in face recognition. Here, we considered five …
images and explored its applications in face recognition. Here, we considered five …
A Systematic Approach for Object Detection in Unconstrained Environments
Object detection in unconstrained environments could be defined as identifying objects
captured in challenging environments like smoky, wild, and cloudy environments. Object …
captured in challenging environments like smoky, wild, and cloudy environments. Object …
Assessing Face Image Quality: A Large-Scale Database and a Transformer Method
The amount of face images has been witnessing an explosive increase in the last decade,
where various distortions inevitably exist on transmitted or stored face images. The …
where various distortions inevitably exist on transmitted or stored face images. The …
Blind image quality prediction for object detection
Automatic video data analysis tools have become indispensable components in today's
imaging applications. The accuracy of automatic analysis methods relies on the quality of …
imaging applications. The accuracy of automatic analysis methods relies on the quality of …
Context prior-based with residual learning for face detection: A deep convolutional encoder–decoder network
In the field of security, faces are usually blurry, occluded, diverse pose and small in the
image captured by an outdoor surveillance camera, which is affected by the external …
image captured by an outdoor surveillance camera, which is affected by the external …
Deep learning for biometric face recognition: experimental study on benchmark data sets
There are still problems in applications of Machine Learning for face recognition. Such
factors as lighting conditions, head rotations, emotions, and view angles affect the …
factors as lighting conditions, head rotations, emotions, and view angles affect the …
Supervised dictionary learning for blind image quality assessment using quality-constraint sparse coding
Blind image quality assessment (BIQA) involves predicting the perceptual quality of distorted
images without using their corresponding reference images as benchmark. Especially, it is …
images without using their corresponding reference images as benchmark. Especially, it is …
Quality aware features for performance prediction and time reduction in video object tracking
The existing body of work on video object tracking (VOT) algorithms has studied various
image conditions such as occlusion, clutter, and object shape, which influence video quality …
image conditions such as occlusion, clutter, and object shape, which influence video quality …
An image quality adjustment framework for object detection on embedded cameras
Automatic analysis tools are ubiquitously applied on wireless embedded cameras to extract
high-level information from raw data. The quality of images may be degraded by factors such …
high-level information from raw data. The quality of images may be degraded by factors such …