Guest
Eduardo Dixo Senior Data Scientist @ Continental Drones with mounted cameras provide significant advantages when compared to fixed cameras for object detection and visual tracking scenarios. Given their recent adoption in the wild and late advances in computer vision models, many aerial datasets have been introduced. In this talk, we’ll explore recent advances in object detection, comparing the challenges of natural images with those recorded by drones. Given the successes achieved by pretraining image classifiers on large datasets, and transferring the learned representations, a set of object detectors fine-tuned on publicly available aerial datasets will be presented and explained. We’ll highlight existing libraries that mitigate the cost of training large models from scratch, by including pretrained model weights and model variants found in the literature. Both Convolutional Neural Networks and the newly developed Transformers applied to vision will be covered and compared, outlining the main features of
