Paper Overview
Qwen2.5-Omni is a groundbreaking end-to-end multimodal foundation model developed by Alibaba Qwen Group. In a unified and streaming manner, itβs designed to perceive and generate across multiple modalities β including
In this blog post we review the YOLOv6 paper, carry out inference using the YOLOv6 models, and also compare YOLOv6 with YOLOv5.
YOLOX object detector is a recent addition in the YOLO family. Read the article for detailed YOLOX paper explanation and learn how to train YOLOX on a custom dataset.
Introduction Super-resolution refers to the process of upscaling or improving the details of the image. Follow this blog to learn the options for Super Resolution in OpenCV. When increasing the
In this post, we will discuss about two Deep Learning based approaches for motion estimation using Optical Flow. FlowNet is the first CNN approach for calculating Optical Flow and RAFT
Depth estimation is a critical task for autonomous driving. Itβs necessary to estimate the distance to cars, pedestrians, bicycles, animals, and obstacles.The popular way to estimate depth is LiDAR. However,
