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Softmax Dissection: Towards Understanding Intra- and Inter-class
  Objective for Embedding Learning

Softmax Dissection: Towards Understanding Intra- and Inter-class Objective for Embedding Learning

4 August 2019
Lanqing He
Zhongdao Wang
Yali Li
Shengjin Wang
ArXivPDFHTML

Papers citing "Softmax Dissection: Towards Understanding Intra- and Inter-class Objective for Embedding Learning"

6 / 6 papers shown
Title
Mitigating Catastrophic Forgetting in the Incremental Learning of Medical Images
Mitigating Catastrophic Forgetting in the Incremental Learning of Medical Images
Sara Yavari
Jacob Furst
CLL
58
0
0
28 Apr 2025
Racial Bias within Face Recognition: A Survey
Racial Bias within Face Recognition: A Survey
Seyma Yucer
Furkan Tektas
Noura Al Moubayed
T. Breckon
FaML
38
10
0
01 May 2023
SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition
Yaoyao Zhong
Weihong Deng
Jiani Hu
Dongyue Zhao
Xian Li
Dongchao Wen
3DH
CVBM
48
87
0
24 May 2022
Training and challenging models for text-guided fashion image retrieval
Training and challenging models for text-guided fashion image retrieval
Eric Dodds
Jack Culpepper
Gaurav Srivastava
18
8
0
23 Apr 2022
Partial FC: Training 10 Million Identities on a Single Machine
Partial FC: Training 10 Million Identities on a Single Machine
Xiang An
Xuhan Zhu
Yanghua Xiao
Lan Wu
Ming Zhang
Yuan Gao
Bin Qin
Debing Zhang
Ying Fu
CVBM
46
214
0
11 Oct 2020
Exploring Racial Bias within Face Recognition via per-subject
  Adversarially-Enabled Data Augmentation
Exploring Racial Bias within Face Recognition via per-subject Adversarially-Enabled Data Augmentation
Seyma Yucer
S. Akçay
Noura Al-Moubayed
T. Breckon
14
61
0
19 Apr 2020
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