Diffusion models are powerful, but they require a lot of time and data to train. We propose
Patch Diffusion, a generic patch-wise training framework, to significantly reduce the training …

Glass surfaces are omnipresent in our daily lives and often go unnoticed by the majority of
us. While humans are generally able to infer their locations and thus avoid collisions, it can …

The self-attention mechanism (SAM) is widely used in various fields of artificial intelligence
and has successfully boosted the performance of different models. However, current …

Channel pruning is a popular technique for compressing convolutional neural networks
(CNNs), where various pruning criteria have been proposed to remove the redundant filters …

Image restoration tasks have witnessed great performance improvement in recent years by
develo** large deep models. Despite the outstanding performance, the heavy …

The remarkable performance of Convolutional Neural Networks (CNNs) has increased their
use in real-time systems and devices with limited resources. Hence, compacting these …

A deep learning model named Cracklab for pixel level segmentation and measurement of
concrete cracks is proposed. Cracklab excels at handling cracks at image edges and …

Deep models are notoriously known to perform poorly when encountering new domains with
different statistics. To alleviate this issue, we present a new domain generalization method …

Real‐time network by adopting attention mechanism is helpful for enhancing lane detection
capability of autonomous vehicles. This paper proposes a real‐time lane detection network …

Recently many plug-and-play self-attention modules (SAMs) are proposed to enhance the
model generalization by exploiting the internal information of deep convolutional neural …