DETR: End-to-End Object Detection with Transformers

The paper

DETR (DEtection TRansformer) is a new method that views object detection as a direct set prediction problem. The approach streamlines the detection pipeline, effectively removing the need for many hand-designed components like non-maximum suppression or anchor generation.

The key idea is to use a transformer encoder-decoder architecture combined with a bipartite matching loss that forces unique predictions.

Review Presentation Slides

Coming soon