Universal Noise Annotation: Unveiling the Impact of Noisy annotation on
Object Detection

Universal Noise Annotation: Unveiling the Impact of Noisy annotation on Object Detection

21 December 2023

Kwang-seok Ryoo

Seungryong Kim

Papers citing "Universal Noise Annotation: Unveiling the Impact of Noisy annotation on Object Detection"

6 / 6 papers shown

Title
YOLO-FEDER FusionNet: A Novel Deep Learning Architecture for Drone Detection Tamara R. Lenhard Andreas Weinmann Stefan Jäger Tobias Koch FedML 32 2 0 17 Jun 2024
DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR Shilong Liu Feng Li Hao Zhang X. Yang Xianbiao Qi Hang Su Jun Zhu Lei Zhang ViT 149 728 0 28 Jan 2022
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 34 122 0 10 Dec 2020
Towards Noise-resistant Object Detection with Noisy Annotations Junnan Li Caiming Xiong R. Socher S. Hoi ObjD NoLa 62 28 0 03 Mar 2020
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,567 0 17 Apr 2017
Feature Pyramid Networks for Object Detection Nayeon Lee Piotr Dollár Ross B. Girshick Kaiming He Bharath Hariharan Serge J. Belongie ObjD 183 21,813 0 09 Dec 2016