In this post, we focus on two mainstreams of one-stage object detection methods: YOLO family and SSD family. Compared to two-stage methods (like R-CNN series), those models skip the region proposal stage and directly extract detection results from feature maps. For that reason, one-stage models are faster but at the cost of reduced accuracy.

In this post, we are looking into two high-resolution image generation models: ProGAN and StyleGAN. They generates the artificial image gradually, starting from a very low resolution and continuing to a high resolution (finally $1024\times 1024​$).