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Do Different Deep Metric Learning Losses Lead to Similar Learned
Features?

Do Different Deep Metric Learning Losses Lead to Similar Learned Features?

IEEE International Conference on Computer Vision (ICCV), 2021

5 May 2022

Konstantin Kobs

ArXiv (abs)PDF HTML

Papers citing "Do Different Deep Metric Learning Losses Lead to Similar Learned Features?"

5 / 5 papers shown

Transparency Techniques for Neural Networks trained on Writer Identification and Writer Verification

Transparency Techniques for Neural Networks trained on Writer Identification and Writer Verification

117

0

0

19 Jun 2025

Getting More for Less: Using Weak Labels and AV-Mixup for Robust
Audio-Visual Speaker Verification

Getting More for Less: Using Weak Labels and AV-Mixup for Robust Audio-Visual Speaker VerificationInterspeech (Interspeech), 2023

Anith Selvakumar

294

1

0

13 Sep 2023

Data-Side Efficiencies for Lightweight Convolutional Neural Networks

Data-Side Efficiencies for Lightweight Convolutional Neural Networks

Lawrence O'Gorman

Michael J. Coss

152

2

0

24 Aug 2023

InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images

InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for ImagesIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2022

Konstantin Kobs

91

8

0

23 Nov 2022

On Background Bias in Deep Metric Learning

On Background Bias in Deep Metric LearningInternational Conference on Machine Vision (ICMV), 2022

Konstantin Kobs

145

1

0

04 Oct 2022