Small Object Detection by DETR via Information Augmentation and Adaptive Feature Fusion-Reference-Cited by-同舟云学术

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Small Object Detection by DETR via Information Augmentation and Adaptive Feature Fusion

Published:2024-06-10 Issue: Volume:89 Page:39-44
ISSN:
Container-title:Proceedings of 2024 ACM ICMR Workshop on Multimodal Video Retrieval
language:
Short-container-title:

Author:

Huang Ji¹^ORCID,Li Tianrui²^ORCID

Affiliation:

1. School of Computing and Artificial Intelligence, Southwest Jiaotong University, China

2. School of Computing and Artificial Intelligence, Southwest Jiaotong University, China and Engineering Research Center of Sustainable Urban Intelligent Transportation, Ministry of Education, China

Funder

the Fundamental Research Funds for the Central Universities

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3664524.3675362

Reference39 articles.

1. Elad Amrani, Rami Ben-Ari, Inbar Shapira, Tal Hakim, and Alex Bronstein. 2020. Self-supervised object detection and retrieval using unlabeled videos. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. 954–955.

2. Cascade R-CNN: Delving Into High Quality Object Detection

3. Nicolas Carion Francisco Massa Gabriel Synnaeve Nicolas Usunier Alexander Kirillov and Sergey Zagoruyko. 2020. End-to-End Object Detection with Transformers. (2020).

4. Enhancing object detection for autonomous driving by optimizing anchor generation and addressing class imbalance

5. Cheng Cui, Ruoyu Guo, Yuning Du, Dongliang He, Fu Li, Zewu Wu, Qiwen Liu, Shilei Wen, Jizhou Huang, Xiaoguang Hu, 2021. Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones. arXiv preprint arXiv:2103.05959 (2021).

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