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Status: Unchecked ×Keyword: transformer encoder-decoder ×Clear all

2 claims from 1 paper

1. Computer Science › Advanced Neural Network Applications

   End-to-End Object Detection with Transformers

   Carion, Massa, Synnaeve, Usunier, Kirillov and Zagoruyko · Lecture notes in computer science · 2020

   The paper presents DETR, which treats object detection as direct set prediction using a transformer, removing hand-designed parts such as non-maximum suppression and anchor generation.

   Unchecked2 claims
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   1. UncheckedDETR, a transformer-based detector, is reported to match the Faster RCNN baseline in accuracy and run-time on the COCO object detection dataset.“DETR demonstrates accuracy and run-time performance on par with the well-established and highly-optimized Faster RCNN baseline on the challenging COCO object detection dataset.”
   2. UncheckedThe DETR object detector can be easily extended to also produce panoptic segmentation, within a single unified model.“Moreover, DETR can be easily generalized to produce panoptic segmentation in a unified manner.”