Vision Transformer
Video Anomaly Detection (VAD) is one of the most challenging problems in computer vision. It involves identifying rare, abnormal events in videos – such as burglary, fighting, or accidents –
What if a radiologist facing a complex scan in the middle of the night could ask an AI assistant for a second opinion, right from their local workstation? This isn't
Zero-shot anomaly detection (ZSAD) is a vital problem in computer vision, particularly in real-world scenarios where labeled anomalies are scarce or unavailable. Traditional vision-language models (VLMs) like CLIP fall short
Dive into NVIDIA's GR00T N1.5, a groundbreaking open foundation model poised to revolutionize humanoid robotics! Discover how this advanced Vision-Language-Action (VLA) model, with its smarter architecture and innovative training using
Imagine you’re a robotics enthusiast, a student, or even a seasoned developer, and you’ve been captivated by the idea of robots that can see, understand our language, and then act on that
Ever watched an AI-generated video and wondered how it was made? Or perhaps dreamed of creating your own dynamic scenes, only to be overwhelmed by the complexity or the need
In the rapidly evolving field of deep learning, the challenge often lies not just in designing powerful models but also in making them accessible and efficient for practical use, especially
In this article, we are fine tuning the TrOCR Small Printed model on the SCUT CTW1500 dataset to improve its performance on curved text.
In this article, we show how to implement Vision Transformer using the PyTorch deep learning library.
