With the advances in scientific foundations and technological implementations, optical
metrology has become versatile problem-solving backbones in manufacturing, fundamental …

Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …

We introduce Token Merging (ToMe), a simple method to increase the throughput of existing
ViT models without needing to train. ToMe gradually combines similar tokens in a …

With the advent of convolutional neural networks, stereo matching algorithms have recently
gained tremendous progress. However, it remains a great challenge to accurately extract …

We present the first systematic study on concealed object detection (COD), which aims to
identify objects that are visually embedded in their background. The high intrinsic similarities …

While deep neural networks achieve great performance on fitting the training distribution, the
learned networks are prone to overfitting and are susceptible to adversarial attacks. In this …

Large scale text-guided diffusion models have garnered significant attention due to their
ability to synthesize diverse images that convey complex visual concepts. This generative …

We present a comprehensive study on a new task named camouflaged object detection
(COD), which aims to identify objects that are" seamlessly" embedded in their surroundings …

Convolutional neural network (CNN), a class of artificial neural networks that has become
dominant in various computer vision tasks, is attracting interest across a variety of domains …

The usage of convolutional neural networks (CNNs) for unsupervised image segmentation
was investigated in this study. Similar to supervised image segmentation, the proposed CNN …