DN-DETR (DeNoising DETR) is an official implementation of a CVPR 2022 Oral paper that introduces query denoising to accelerate DETR (DEtection TRansformer) training. The method applies denoising techniques to transformer queries during training to improve convergence speed and detection accuracy. The repository includes training code, model weights, and extensions to other DETR variants including Mask2Former and Faster R-CNN.