mlsanityData to 14 Oct 2026

ICME 2022 Few-shot LOGO detection top 9 solution

arXiv 2206.11462 ↗First posted 23 Jun 2022cs.CV cs.AIcited by 1

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Abstract (arXiv)

ICME-2022 few-shot logo detection competition is held in May, 2022. Participants are required to develop a single model to detect logos by handling tiny logo instances, similar brands, and adversarial images at the same time, with limited annotations. Our team achieved rank 16 and 11 in the first and second round of the competition respectively, with a final rank of 9th. This technical report summarized our major techniques used in this competitions, and potential improvement.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 6 references that are in the map. First posted on arXiv 23 Jun 2022.

Builds on

6 of 6 references.

References · 6

  1. 2019RandAugment: Practical automated data augmentation with a reduced search spacecited by 2,269
  2. 2019MMDetection: Open MMLab Detection Toolbox and Benchmarkcited by 1,385
  3. 2017Cascade R-CNN: Delving into High Quality Object Detectioncited by 1,276
  4. 2020Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentationcited by 596
  5. 2019Res2Net: A New Multi-scale Backbone Architecturecited by 470
  6. 2019Libra R-CNN: Towards Balanced Learning for Object Detectioncited by 255

Built on by

Cited by year

Citing papers per year: 2022: 1.

1 paper.

  1. 2022Deep Learning for Logo Detection: A Surveycited by 8