# RL-LOGO: Deep Reinforcement Learning Localization for Logo Recognition

arXiv: https://arxiv.org/abs/2312.16792 · HTML: https://mlsanity.com/paper/2312.16792/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 19 references that are in the map.
- First posted on arXiv 28 Dec 2023.

## Builds on (most cited first, 12 of 12)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [Bag of Tricks for Image Classification with Convolutional Neural Networks](https://mlsanity.com/paper/1812.01187/) (2018)
- [Learning to Navigate for Fine-grained Classification](https://mlsanity.com/paper/1809.00287/) (2018)
- [Active Object Localization with Deep Reinforcement Learning](https://mlsanity.com/paper/1511.06015/) (2015)
- [DTrOCR: Decoder-only Transformer for Optical Character Recognition](https://mlsanity.com/paper/2308.15996/) (2023)
- [LogoDet-3K: A Large-Scale Image Dataset for Logo Detection](https://mlsanity.com/paper/2008.05359/) (2020)
- [Logo-2K+: A Large-Scale Logo Dataset for Scalable Logo Classification](https://mlsanity.com/paper/1911.07924/) (2019)
- [Deep Learning for Logo Detection: A Survey](https://mlsanity.com/paper/2210.04399/) (2022)
- [Scalable Logo Recognition using Proxies](https://mlsanity.com/paper/1811.08009/) (2018)
- [DiffusionSTR: Diffusion Model for Scene Text Recognition](https://mlsanity.com/paper/2306.16707/) (2023)
- [A3S: Adversarial learning of semantic representations for Scene-Text Spotting](https://mlsanity.com/paper/2302.10641/) (2023)

## Built on by (most cited first, 4 of 4)

- [IMAGGarment: Fine-Grained Garment Generation for Controllable Fashion Design](https://mlsanity.com/paper/2504.13176/) (2025)
- [Policy Gradient-Driven Noise Mask](https://mlsanity.com/paper/2406.14568/) (2024)
- [JSTR: Judgment Improves Scene Text Recognition](https://mlsanity.com/paper/2404.05967/) (2024)
- [VersaVogue: Visual Expert Orchestration and Preference Alignment for Unified Fashion Synthesis](https://mlsanity.com/paper/2604.07210/) (2026)

## Abstract (arXiv)

This paper proposes a novel logo image recognition approach incorporating a localization technique based on reinforcement learning. Logo recognition is an image classification task identifying a brand in an image. As the size and position of a logo vary widely from image to image, it is necessary to determine its position for accurate recognition. However, because there is no annotation for the position coordinates, it is impossible to train and infer the location of the logo in the image. Therefore, we propose a deep reinforcement learning localization method for logo recognition (RL-LOGO). It utilizes deep reinforcement learning to identify a logo region in images without annotations of the positions, thereby improving classification accuracy. We demonstrated a significant improvement in accuracy compared with existing methods in several published benchmarks. Specifically, we achieved an 18-point accuracy improvement over competitive methods on the complex dataset Logo-2K+. This demonstrates that the proposed method is a promising approach to logo recognition in real-world applications.