The prompt detection of early decay in the pavement could be an auspicious technique in
road maintenance. Admittedly, early crack detection allows preventive measures to be taken …

Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

Abstract We introduce the Segment Anything (SA) project: a new task, model, and dataset for
image segmentation. Using our efficient model in a data collection loop, we built the largest …

We present ControlNet, a neural network architecture to add spatial conditioning controls to
large, pretrained text-to-image diffusion models. ControlNet locks the production-ready large …

ChatGPT is attracting a cross-field interest as it provides a language interface with
remarkable conversational competency and reasoning capabilities across many domains …

Text-to-Image diffusion models have made tremendous progress over the past two years,
enabling the generation of highly realistic images based on open-domain text descriptions …

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 …

Global context information is essential for the semantic segmentation of remote sensing (RS)
images. However, most existing methods rely on a convolutional neural network (CNN) …

The most advanced text-to-image (T2I) models require significant training costs (eg, millions
of GPU hours), seriously hindering the fundamental innovation for the AIGC community …

The class activation maps are generated from the final convolutional layer of CNN. They can
highlight discriminative object regions for the class of interest. These discovered object …