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AutoNovel: Automatically Discovering and Learning Novel Visual
  Categories

AutoNovel: Automatically Discovering and Learning Novel Visual Categories

29 June 2021
Kai Han
Sylvestre-Alvise Rebuffi
Sébastien Ehrhardt
Andrea Vedaldi
Andrew Zisserman
    SSL
ArXivPDFHTML

Papers citing "AutoNovel: Automatically Discovering and Learning Novel Visual Categories"

28 / 78 papers shown
Title
NEV-NCD: Negative Learning, Entropy, and Variance regularization based
  novel action categories discovery
NEV-NCD: Negative Learning, Entropy, and Variance regularization based novel action categories discovery
Zahid Hasan
Masud Ahmed
A. Faridee
S. Purushotham
H. Kwon
Hyungtae Lee
Nirmalya Roy
13
2
0
14 Apr 2023
CiPR: An Efficient Framework with Cross-instance Positive Relations for
  Generalized Category Discovery
CiPR: An Efficient Framework with Cross-instance Positive Relations for Generalized Category Discovery
Shaozhe Hao
Kai Han
Kwan-Yee Kenneth Wong
38
16
0
14 Apr 2023
What's in a Name? Beyond Class Indices for Image Recognition
What's in a Name? Beyond Class Indices for Image Recognition
Kai Han
Yandong Li
S. Vaze
Jie Li
Xuhui Jia
VLM
19
7
0
05 Apr 2023
Dynamic Conceptional Contrastive Learning for Generalized Category
  Discovery
Dynamic Conceptional Contrastive Learning for Generalized Category Discovery
Nan Pu
Zhun Zhong
N. Sebe
16
60
0
30 Mar 2023
Novel Class Discovery: an Introduction and Key Concepts
Novel Class Discovery: an Introduction and Key Concepts
Colin Troisemaine
V. Lemaire
Stéphane Gosselin
Alexandre Reiffers-Masson
Joachim Flocon-Cholet
Sandrine Vaton
32
21
0
22 Feb 2023
Transferable Deep Metric Learning for Clustering
Transferable Deep Metric Learning for Clustering
C. SimoAlami
Rim Kaddah
Jesse Read
25
0
0
13 Feb 2023
Parametric Information Maximization for Generalized Category Discovery
Parametric Information Maximization for Generalized Category Discovery
Florent Chiaroni
Jose Dolz
Imtiaz Masud Ziko
A. Mitiche
Ismail Ben Ayed
27
16
0
01 Dec 2022
Découvrir de nouvelles classes dans des données tabulaires
Découvrir de nouvelles classes dans des données tabulaires
Colin Troisemaine
Joachim Flocon-Cholet
Stéphane Gosselin
Sandrine Vaton
Alexandre Reiffers-Masson
Vincent Lemaire
15
0
0
28 Nov 2022
Parametric Classification for Generalized Category Discovery: A Baseline
  Study
Parametric Classification for Generalized Category Discovery: A Baseline Study
Xin Wen
Bingchen Zhao
Xiaojuan Qi
35
67
0
21 Nov 2022
Grow and Merge: A Unified Framework for Continuous Categories Discovery
Grow and Merge: A Unified Framework for Continuous Categories Discovery
Xinwei Zhang
Jianwen Jiang
Yutong Feng
Zhi-Fan Wu
Xibin Zhao
Hai Wan
Mingqian Tang
Rong Jin
Yue Gao
CLL
36
29
0
09 Oct 2022
A Closer Look at Novel Class Discovery from the Labeled Set
A Closer Look at Novel Class Discovery from the Labeled Set
Ziyun Li
Jona Otholt
Ben Dai
Diane Hu
Christoph Meinel
Haojin Yang
BDL
15
12
0
19 Sep 2022
A Method for Discovering Novel Classes in Tabular Data
A Method for Discovering Novel Classes in Tabular Data
Colin Troisemaine
Joachim Flocon-Cholet
Stéphane Gosselin
Sandrine Vaton
Alexandre Reiffers-Masson
V. Lemaire
18
6
0
02 Sep 2022
How does the degree of novelty impacts semi-supervised representation
  learning for novel class retrieval?
How does the degree of novelty impacts semi-supervised representation learning for novel class retrieval?
Q. Leroy
Olivier Buisson
Alexis Joly
SSL
19
0
0
17 Aug 2022
Automatically Discovering Novel Visual Categories with Self-supervised
  Prototype Learning
Automatically Discovering Novel Visual Categories with Self-supervised Prototype Learning
Lu Zhang
Lu Qi
Xu Yang
Hong Qiao
Ming Yang
Zhiyong Liu
SSL
30
3
0
01 Aug 2022
Mutual Information-guided Knowledge Transfer for Novel Class Discovery
Chuyu Zhang
Chuanyan Hu
Ruijie Xu
Zhitong Gao
Qian He
Xuming He
18
4
0
24 Jun 2022
Spacing Loss for Discovering Novel Categories
Spacing Loss for Discovering Novel Categories
K. J. Joseph
S. Paul
Gaurav Aggarwal
Soma Biswas
Piyush Rai
Kai Han
V. Balasubramanian
14
14
0
22 Apr 2022
Unseen Object Instance Segmentation with Fully Test-time RGB-D
  Embeddings Adaptation
Unseen Object Instance Segmentation with Fully Test-time RGB-D Embeddings Adaptation
Lu Zhang
Siqi Zhang
Xu Yang
Hong Qiao
Zhiyong Liu
19
11
0
21 Apr 2022
Towards Open-Set Object Detection and Discovery
Towards Open-Set Object Detection and Discovery
Jiyang Zheng
Weihao Li
Jie Hong
L. Petersson
Nick Barnes
ObjD
30
61
0
12 Apr 2022
Generalized Category Discovery
Generalized Category Discovery
S. Vaze
Kai Han
Andrea Vedaldi
Andrew Zisserman
24
188
0
07 Jan 2022
Learning Representation for Clustering via Prototype Scattering and
  Positive Sampling
Learning Representation for Clustering via Prototype Scattering and Positive Sampling
Zhizhong Huang
Jie Chen
Junping Zhang
Hongming Shan
21
87
0
23 Nov 2021
Open-Set Recognition: a Good Closed-Set Classifier is All You Need?
Open-Set Recognition: a Good Closed-Set Classifier is All You Need?
S. Vaze
Kai Han
Andrea Vedaldi
Andrew Zisserman
BDL
169
404
0
12 Oct 2021
A Unified Objective for Novel Class Discovery
A Unified Objective for Novel Class Discovery
Enrico Fini
E. Sangineto
Stéphane Lathuilière
Zhun Zhong
Moin Nabi
Elisa Ricci
23
168
0
19 Aug 2021
Novel Visual Category Discovery with Dual Ranking Statistics and Mutual
  Knowledge Distillation
Novel Visual Category Discovery with Dual Ranking Statistics and Mutual Knowledge Distillation
Bingchen Zhao
Kai Han
15
106
0
07 Jul 2021
Joint Representation Learning and Novel Category Discovery on Single-
  and Multi-modal Data
Joint Representation Learning and Novel Category Discovery on Single- and Multi-modal Data
Xu Jia
Kai Han
Yukun Zhu
Bradley Green
147
57
0
26 Apr 2021
Meta Discovery: Learning to Discover Novel Classes given Very Limited
  Data
Meta Discovery: Learning to Discover Novel Classes given Very Limited Data
Haoang Chi
Feng Liu
Bo Han
Wenjing Yang
L. Lan
Tongliang Liu
Gang Niu
Mingyuan Zhou
Masashi Sugiyama
26
42
0
08 Feb 2021
LSD-C: Linearly Separable Deep Clusters
LSD-C: Linearly Separable Deep Clusters
Sylvestre-Alvise Rebuffi
Sébastien Ehrhardt
Kai Han
Andrea Vedaldi
Andrew Zisserman
19
24
0
17 Jun 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
267
3,369
0
09 Mar 2020
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
261
1,275
0
06 Mar 2017
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