Discussing YOLOX and YOLOR

Regarding YOLOX the general agreement is that the paper is great. The main added value of this paper is grouping the latest improvements in object detection for single shot detection (SSD). We personally thing the most important contribution where removing anchors and nms and the approach to improve training signal by multiple positives. It is hard to write down all the possitives effects that these changes bring.

Papers that would be interesting to understand specific points are:

“Ota: Optimal transport assignment for object detection.”
“Object detection made simpler by eliminating heuristic nms.”
“Fcos: Fully convolutional one-stage object detection”

There was mainly one conclusion from YOLOR: The idea is interesting and should be explorer further by the comunity, the execution was mediocre. comunication was poor and it is missing a lot of important details to have a proper conversation of this topic.