Paper Overview

Qwen2.5-Omni: A Real-Time Multimodal AI

Qwen2.5-Omni is a groundbreaking end-to-end multimodal foundation model developed by Alibaba Qwen Group. In a unified and streaming manner, it’s designed to perceive and generate across multiple modalities – including

Generative Models, Multimodal Models, Paper Overview

YOLOv6 Object Detection – Paper Explanation and Inference

In this blog post we review the YOLOv6 paper, carry out inference using the YOLOv6 models, and also compare YOLOv6 with YOLOv5.

Computer Vision, Deep Learning, Object Detection, Paper Overview, YOLO

YOLOX Object Detector Paper Explanation and Custom Training

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.

CNN, Paper Overview, YOLO

Super Resolution in OpenCV

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

Computer Vision, Deep Learning, Image Processing, OpenCV Tutorials, Paper Overview

RAFT: Optical Flow estimation using Deep Learning

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

Deep Learning, Paper Overview, PyTorch, Video Analysis

Depth Estimation Using Stereo Matching

Depth estimation is a critical task for autonomous driving. It’s necessary to estimate the distance to cars, pedestrians, bicycles, animals, and obstacles.The popular way to estimate depth is LiDAR. However,

Deep Learning, Paper Overview, PyTorch