With applications such as object detection, segmentation, and captioning, the COCO dataset is widely understood by state-of-the-art neural networks. Its versatility and multi-purpose scene variation serve best to train a computer vision model and benchmark its performance. In this post, we will dive deeper into COCO fundamentals, covering the following: What is COCO? COCO classes What is […]
7 Key Considerations to Develop a Scalable Annotation Pipeline
Whether for medical imaging, autonomous driving, agriculture automation, or robotics, scaling a computer vision (CV) project is tough and takes tons of micromanaging, tracking, and analysis for the best results. The data is usually annotated in batches because of the volume and multiplicity of iterations needed along the way. The batches undergo several revisions for […]
OpenCV AI Competition 2021 Highlights and Team Profiles Part 4
It’s been a few weeks since our last post, but things have definitely not slowed down in OpenCV AI Competition 2021! We’ve got a slew of highlights in this post, as well as interviews with two more of the amazing teams in this worldwide competition. In this post we’re featuring a short question and answer […]
Evaluating OpenCV’s new RANSACs
Spoiler: They’re much better now! OpenCV RANSAC is dead. Long live the OpenCV USAC! Last year a group of researchers including myself from UBC, Google, CTU in Prague and EPFL published a paper “Image Matching across Wide Baselines: From Paper to Practice“, which, among other messages, has shown that OpenCV RANSAC for fundamental matrix estimation […]