Deep neural models, in recent years, have been successful in almost every field, even
solving the most complex problem statements. However, these models are huge in size with …

Previous arts built an intimate link between knowledge distillation (KD) and label smoothing
(LS) that they both impose regularization on the model training. In this paper, we delve …

Convolutional neural networks have an immense impact on computer vision tasks. However,
the accuracy of convolutional neural networks on a dataset is tremendously affected when …

With the advancement of artificial intelligence, 3D human pose estimation-based systems for
sports training and posture correction have gained significant attention in adolescent sports …

Falls are a major health threat for older people. A timely assistance can reduce the extent of
physical injury caused by the falls. Currently, low-cost and convenient video surveillance …

Image and video tools for analyzing crop scenes and plants are essential for applying
precision agriculture to crop maintenance, harvesting, or pruning. In this paper, we are …

This paper presents a novel Convolutional Neural Network (CNN) architecture for 2D human
pose estimation from RGB images that balances between high 2D human pose/skeleton …

Convolutional neural networks (CNNs) have demonstrated excellent capability in various
visual recognition tasks but impose an excessive computational burden. The latter problem …

Recent online knowledge distillation (OKD) methods focus on capturing rich and useful
intermediate information by performing multi-layer feature learning. Existing works only …

Human pose estimation is a fundamental yet challenging task in computer vision. However,
difficult scenarios such as invisible keypoints, occlusions and small-scale persons are still …