PyTorch has extensive capabilities for computer vision tasks such as image classification, object detection, and image segmentation. It is widely used in industries like autonomous vehicles, medical imaging, and surveillance systems to develop sophisticated algorithms and models for better understanding and interpreting visual data.

In computer vision, PyTorch provides pre-trained models like ResNet, AlexNet, and VGG, which can be fine-tuned and used for various tasks. Additionally, PyTorch is equipped with powerful tools like torchvision, which simplifies the process of loading and preprocessing datasets, thus making it easier to train deep learning models for computer vision applications.