A picture is worth a thousand words! As computer vision and machine learning experts, we could not agree more. Human intuition is the most powerful way of making sense out of random chaos, ...
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 ...
How To Run Inference Using TensorRT C++ API
In this post, we continue to consider how to speed up inference quickly and painlessly if we already have a trained model in PyTorch. In the previous post We discussed what ONNX and TensorRT are ...
Bag of Tricks for Image Classification
Introduction Image classification is a key task in Computer Vision. In an image classification task, the input is an image, and the output is a class label (e.g. "cat", "dog", etc. ) that ...
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. ...
Stanford MRNet Challenge: Classifying Knee MRIs
Stanford ML Group, led by Andrew Ng, works on important problems in areas such as healthcare and climate change, using AI. Last year they released a knee MRI dataset consisting of 1,370 knee MRI ...