Hot papers on arXiv from the past month – May 2020

Here are the most tweeted papers that were uploaded onto arXiv during May 2020. Results are powered by Arxiv Sanity Preserver. Abstract: We present a new method that views object detection as a direct set prediction problem. Our approach streamlines the detection pipeline, effectively removing the need for many hand-designed components like a non-maximum suppression procedure or anchor generation that explicitly encode our prior knowledge about the task. The main ingredients of the new framework, called DEtection TRansformer or DETR, are a set-based global loss that forces unique predictions via bipartite matching, and a transformer encoder-decoder architecture.