FCOS: Fully Convolutional One-stage Object Detection is an anchor-free (anchorless) object detector. It solves object detection problems in a per-pixel prediction fashion, similar to segmentation. ...
YOLOv7 Pose vs MediaPipe in Human Pose Estimation
YOLOv7 Pose was introduced in the YOLOv7 repository a few days after the initial release in July ‘22. It is a single-stage, multi-person pose estimation model. YOLOv7 pose is unique, as it deviates ...
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 ...
Document Segmentation Using Deep Learning in PyTorch
Document Scanning is a background segmentation problem that can be solved using various methods. It is one of the extensively used applications of computer vision. In this article, we are considering ...
Mean Average Precision (mAP) in Object Detection
Mean Average Precision (mAP) is a performance metric used for evaluating machine learning models. It is the most popular metric that is used by benchmark challenges such as PASCAL VOC, COCO, ImageNET ...
YOLOv7 Object Detection Paper Explanation & Inference
What is YOLOv7? YOLOv7 is a single-stage real-time object detector. It was introduced to the YOLO family in July'22. According to the YOLOv7 paper, it is the fastest and most accurate real-time ...
