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Mean-Shifted Contrastive Loss for Anomaly Detection

Mean-Shifted Contrastive Loss for Anomaly Detection

7 June 2021
Tal Reiss
Yedid Hoshen
ArXivPDFHTML

Papers citing "Mean-Shifted Contrastive Loss for Anomaly Detection"

28 / 28 papers shown
Title
PathoSCOPE: Few-Shot Pathology Detection via Self-Supervised Contrastive Learning and Pathology-Informed Synthetic Embeddings
Sinchee Chin
Yinuo Ma
Xiaochen Yang
Jing-Hao Xue
Wenming Yang
SSL
MedIm
37
0
0
23 May 2025
When Unsupervised Domain Adaptation meets One-class Anomaly Detection: Addressing the Two-fold Unsupervised Curse by Leveraging Anomaly Scarcity
When Unsupervised Domain Adaptation meets One-class Anomaly Detection: Addressing the Two-fold Unsupervised Curse by Leveraging Anomaly Scarcity
Nesryne Mejri
Enjie Ghorbel
Anis Kacem
Pavel Chernakov
Niki Maria Foteinopoulou
Djamila Aouada
86
0
0
28 Feb 2025
Killing it with Zero-Shot: Adversarially Robust Novelty Detection
Hossein Mirzaei
Mohammad Jafari
Hamid Reza Dehbashi
Zeinab Sadat Taghavi
Mohammad Sabokrou
M. Rohban
101
1
0
28 Jan 2025
Set Features for Anomaly Detection
Set Features for Anomaly Detection
Niv Cohen
Issar Tzachor
Yedid Hoshen
109
0
0
24 Nov 2023
Understanding the Behaviour of Contrastive Loss
Understanding the Behaviour of Contrastive Loss
Feng Wang
Huaping Liu
SSL
77
679
0
15 Dec 2020
Exploring Simple Siamese Representation Learning
Exploring Simple Siamese Representation Learning
Xinlei Chen
Kaiming He
SSL
192
3,992
0
20 Nov 2020
Learning and Evaluating Representations for Deep One-class
  Classification
Learning and Evaluating Representations for Deep One-class Classification
Kihyuk Sohn
Chun-Liang Li
Jinsung Yoon
Minho Jin
Tomas Pfister
SSL
107
199
0
04 Nov 2020
PANDA: Adapting Pretrained Features for Anomaly Detection and
  Segmentation
PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation
Tal Reiss
Niv Cohen
Liron Bergman
Yedid Hoshen
45
249
0
12 Oct 2020
CSI: Novelty Detection via Contrastive Learning on Distributionally
  Shifted Instances
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances
Jihoon Tack
Sangwoo Mo
Jongheon Jeong
Jinwoo Shin
OODD
36
595
0
16 Jul 2020
Bootstrap your own latent: A new approach to self-supervised Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Jean-Bastien Grill
Florian Strub
Florent Altché
Corentin Tallec
Pierre Harvey Richemond
...
M. G. Azar
Bilal Piot
Koray Kavukcuoglu
Rémi Munos
Michal Valko
SSL
276
6,718
0
13 Jun 2020
Rethinking Assumptions in Deep Anomaly Detection
Rethinking Assumptions in Deep Anomaly Detection
Lukas Ruff
Robert A. Vandermeulen
Billy Joe Franks
Klaus-Robert Muller
Marius Kloft
57
89
0
30 May 2020
Understanding Contrastive Representation Learning through Alignment and
  Uniformity on the Hypersphere
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Tongzhou Wang
Phillip Isola
SSL
99
1,808
0
20 May 2020
Classification-Based Anomaly Detection for General Data
Classification-Based Anomaly Detection for General Data
Liron Bergman
Yedid Hoshen
42
348
0
05 May 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
423
3,397
0
09 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
255
18,607
0
13 Feb 2020
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
113
12,007
0
13 Nov 2019
Object Detection in Optical Remote Sensing Images: A Survey and A New
  Benchmark
Object Detection in Optical Remote Sensing Images: A Survey and A New Benchmark
Ke Li
G. Wan
Gong Cheng
L. Meng
Junwei Han
35
1,433
0
31 Aug 2019
Detecting semantic anomalies
Detecting semantic anomalies
Faruk Ahmed
Aaron Courville
36
83
0
13 Aug 2019
Using Self-Supervised Learning Can Improve Model Robustness and
  Uncertainty
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
Dan Hendrycks
Mantas Mazeika
Saurav Kadavath
D. Song
OOD
SSL
31
940
0
28 Jun 2019
Deep Anomaly Detection Using Geometric Transformations
Deep Anomaly Detection Using Geometric Transformations
I. Golan
Ran El-Yaniv
64
603
0
28 May 2018
Unsupervised Representation Learning by Predicting Image Rotations
Unsupervised Representation Learning by Predicting Image Rotations
Spyros Gidaris
Praveer Singh
N. Komodakis
OOD
SSL
DRL
198
3,272
0
21 Mar 2018
Learning Deep Features for One-Class Classification
Learning Deep Features for One-Class Classification
Pramuditha Perera
Vishal M. Patel
98
370
0
16 Jan 2018
Overcoming catastrophic forgetting in neural networks
Overcoming catastrophic forgetting in neural networks
J. Kirkpatrick
Razvan Pascanu
Neil C. Rabinowitz
J. Veness
Guillaume Desjardins
...
A. Grabska-Barwinska
Demis Hassabis
Claudia Clopath
D. Kumaran
R. Hadsell
CLL
268
7,410
0
02 Dec 2016
What makes ImageNet good for transfer learning?
What makes ImageNet good for transfer learning?
Minyoung Huh
Pulkit Agrawal
Alexei A. Efros
OOD
SSeg
VLM
SSL
92
675
0
30 Aug 2016
Unsupervised Learning of Visual Representations by Solving Jigsaw
  Puzzles
Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles
M. Noroozi
Paolo Favaro
SSL
135
2,973
0
30 Mar 2016
Colorful Image Colorization
Colorful Image Colorization
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
112
3,527
0
28 Mar 2016
Learning Representations for Automatic Colorization
Learning Representations for Automatic Colorization
Gustav Larsson
Michael Maire
Gregory Shakhnarovich
VLM
SSL
69
1,012
0
22 Mar 2016
Deep multi-scale video prediction beyond mean square error
Deep multi-scale video prediction beyond mean square error
Michaël Mathieu
Camille Couprie
Yann LeCun
GAN
107
1,880
0
17 Nov 2015
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