Learn how the annotations for images are stored in the COCO annotation format (used by fastai) — The COCO (Common Objects in Context) format is a commonly used and popular data format for object detection and segmentation. It uses a JSON file to store annotations for each image in a dataset. In this article, I want to explain how the COCO format represents your data for annotation…

Is there something inherently wrong with larger Batch sizes? — Batch Size is among the important hyperparameters in Machine Learning. It is the hyperparameter that defines the number of samples to work through before updating the internal model parameters. The batch size can make or break the performance of many deep learning-based neural networks. Therefore it should not come as…

This is a longer blogpost where I discuss results of experiments I ran myself. In this experiment, I investigate the effect of batch size on training dynamics. The metric we will focus on is the generalization gap which is defined as the difference between the train-time value and test-time value…

Different aspects that you care about — Join 31K+ AI People keeping in touch with the most important ideas in Machine Learning through my free newsletter over here Batch Size is among the important hyperparameters in Machine Learning. It is the hyperparameter that defines the number of samples to work through before updating the internal model parameters…

Human Pose Estimation refers to the process of inferring poses/locating body joints of humans in an image/video. It is one of the most active areas of research in computer vision because of its diverse applications: Gait/Posture Analysis Activity recognition Animation/Gaming Virtual/Augmented reality Surveillance Due to recent advances in deep learning…

Microsoft Research Asia and University of Science and Technology of China have jointly released a new human pose estimation model which has set records on three COCO benchmarks. The neural network “HRNet” features a distinctive parallel structure that can maintain high-resolution representations throughout the entire representative process. HRNet (High Resolution…

Proposes Light Weight HRNet Using Conditional Channel Weighting (CCW) — Lite-HRNet: A Lightweight High-Resolution Network, Lite-HRNet, by Huazhong University of Science and Technology, and Microsoft, 2021 CVPR, Over 130 Citations (Sik-Ho Tsang @ Medium) Human Pose Estimation 2014 … 2018 [PersonLab] 2019 [HRNet / HRNetV1] 2021 [HRNetV2, HRNetV2p] Semantic Segmentation 2014 … 2022 [PVTv2] [YOLACT++] ==== My Other Paper Readings Are Also Over Here…

ResNet-50 is a convolutional neural network that is 50 layers deep. ResNet, short for Residual Networks is a classic neural network used as a backbone for many computer vision tasks. The fundamental breakthrough with ResNet was it allowed us to train extremely deep neural networks with 150+layers. …

Explaining how ResNet-50 works and why it is so popular — Introduction The ResNet architecture is considered to be among the most popular Convolutional Neural Network architectures around. Introduced by Microsoft Research in 2015, Residual Networks (ResNet in short) broke several records when it was first introduced in this paper by He. et. al. Why ResNet? The requirement for a model like ResNet arose…

Revealing whats behind the state-of-the art algorithm HRNet — Outline of HRNet explained: What is HRNet? (short explanation, further down is full explanation) Areas of Application Lets Dive into Convolutional Neural Network How does the HRNet work? Conclusion If you know already the basics (CNN + Areas of Application), skip down to section 3 or section 4. What is HRNet? HRNet is…

In this post we’ll discuss the YOLO detection network and its versions 1, 2 and especially 3. In 2016 Redmon, Divvala, Girschick and Farhadi revolutionized object detection with a paper titled: You Only Look Once: Unified, Real-Time Object Detection. In the paper they introduced a new approach to object detection…

This article will tackle the subject of pose estimation and will analyze how it works and compare different approaches and their pros and cons in regards to computer vision. We will also analyze applications of this cool technology What is Pose Estimation? Simply put, pose estimation is the localization of human joints in either…