As the ML6 special unit for computer vision, our goal is to keep in touch with the latest developments in the field and share our learnings with colleagues, customers, the open-source community, and the public at large. Some areas we are active in at the moment are:
Develop custom, high-performance machine learning models for detecting objects at high speed, at high resolutions, and in challenging real-world circumstances. Different use cases demand different approaches to data pre-processing, modeling, tuning and setup.
Use object tracking across frames to support object detection and segmentation. Detect phenomena or activities that can only be recognized taking the entire stream of images into account. Video analysis presents unique challenges in terms of resource management and model architecture.
Neural networks can transfer faces, poses, stylistic attributes or can generate unseen instances of faces, people, objects or even artworks based on examples.
We are only scratching the surface of the potential in generative modeling in media but also design, retail and other areas. For more information, visit gener8.ai
Processing video on edge, near the camera can reduce network traffic and increase data security. The subsidised Vlaio project Edge Video Analysis (EVA) aims to develop a high-performing solution for anonymization and re-identification on edge. Edge processing presents a number of challenges in terms of performance, architecture, ops and security.