ResearchTrend.AI
The Equalization Losses: Gradient-Driven Training for Long-tailed Object Recognition

The Equalization Losses: Gradient-Driven Training for Long-tailed Object Recognition

Jingru Tan
Yue Liu
Xin Lu
Yongqiang Yao
F. Yu
Tong He
Wanli Ouyang
ArXiv (abs)PDFHTMLGithub (432★)

Papers citing "The Equalization Losses: Gradient-Driven Training for Long-tailed Object Recognition"

2 / 2 papers shown
Title
MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images
MoMBS: Mixed-order minibatch sampling enhances model training from diverse-quality images
Han Li
Hu Han
S.Kevin Zhou
73
0
0
24 May 2025
Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax
Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax
Yu Li
Tao Wang
Bingyi Kang
Sheng Tang
Chunfeng Wang
Jintao Li
Jiashi Feng
164
267
0
18 Jun 2020

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.