In the realm of computer vision, Deep Convolutional Neural Networks (DCNNs) have
demonstrated excellent performance. Video Processing, Object Detection, Image …

Object detection is one of the most fundamental and challenging tasks to locate objects in
images and videos. Over the past, it has gained much attention to do more research on …

In this paper, we present a systematic review and evaluation of existing single-image low-
light enhancement algorithms. Besides the commonly used low-level vision oriented …

Recent advances in deep learning have led to the development of accurate and efficient
models for various computer vision applications such as classification, segmentation, and …

Dark environment becomes a challenge for computer vision algorithms owing to insufficient
photons and undesirable noises. Most of the existing studies tackle this by either targeting …

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 …

The availability of large annotated datasets and affordable computation power have led to
impressive improvements in the performance of convolutional neural networks (CNNs) on …

Adverse weather conditions such as haze and rain corrupt the quality of captured images,
which cause detection networks trained on clean images to perform poorly on these …

Face detection is a crucial first step in many facial recognition and face analysis systems.
Early approaches for face detection were mainly based on classifiers built on top of hand …

Recent progress in deep learning has led to accurate and efficient generic object detection
networks. Training of highly reliable models depends on large datasets with highly textured …