DeepLab models, first debuted in ICLR ‘14, are a series of deep learning architectures designed to tackle the problem of semantic segmentation. After making iterative refinements through the years, ...
YOLOv6 Object Detection – Paper Explanation and Inference
YOLO models have become ubiquitous in the world of deep learning, computer vision, and object detection. If you are working on object detection, then there is a high chance that you have used one of ...
YOLOX Object Detector Paper Explanation and Custom Training
What is YOLOX? YOLOX is a single-stage real-time object detector. It was introduced in the paper YOLOX: Exceeding YOLO Series in 2021. The baseline model of YOLOX is YOLOv3 SPP with Darknet53 ...
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 ...
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 which is the ...
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. ...
