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AFAN: Augmented Feature Alignment Network for Cross-Domain Object
  Detection

AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection

10 June 2021
Hongsong Wang
Tianran Ouyang
Ling Shao
ArXiv (abs)PDFHTML

Papers citing "AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection"

31 / 31 papers shown
Title
Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation
Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation
Yangtao Zheng
Di Huang
Songtao Liu
Yunhong Wang
ObjD
227
201
0
23 Mar 2020
Exploring Categorical Regularization for Domain Adaptive Object
  Detection
Exploring Categorical Regularization for Domain Adaptive Object Detection
Chang-Dong Xu
Xingjie Zhao
Xin Jin
Xiu-Shen Wei
OODObjD
209
288
0
20 Mar 2020
Harmonizing Transferability and Discriminability for Adapting Object
  Detectors
Harmonizing Transferability and Discriminability for Adapting Object Detectors
Chaoqi Chen
Zebiao Zheng
Xinghao Ding
Yue Huang
Qi Dou
97
276
0
13 Mar 2020
Improve Unsupervised Domain Adaptation with Mixup Training
Improve Unsupervised Domain Adaptation with Mixup Training
Shen Yan
Huan Song
Nanxiang Li
Lincan Zou
Liu Ren
100
234
0
03 Jan 2020
Adversarial Domain Adaptation with Domain Mixup
Adversarial Domain Adaptation with Domain Mixup
Minghao Xu
Jian Zhang
Bingbing Ni
Teng Li
Chengjie Wang
Qi Tian
Wenjun Zhang
70
447
0
04 Dec 2019
Self-Training and Adversarial Background Regularization for Unsupervised
  Domain Adaptive One-Stage Object Detection
Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection
Seunghyeon Kim
Jaehoon Choi
Taekyung Kim
Changick Kim
85
192
0
02 Sep 2019
Multi-level Domain Adaptive learning for Cross-Domain Detection
Multi-level Domain Adaptive learning for Cross-Domain Detection
Rongchang Xie
Fei Yu
Jiachao Wang
Yizhou Wang
Li Zhang
ObjDOOD
88
93
0
26 Jul 2019
Semi-Supervised Learning by Augmented Distribution Alignment
Semi-Supervised Learning by Augmented Distribution Alignment
Qin Wang
Wen Li
Luc Van Gool
82
70
0
20 May 2019
Diversify and Match: A Domain Adaptive Representation Learning Paradigm
  for Object Detection
Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection
Taekyung Kim
Minki Jeong
Seunghyeon Kim
Seokeon Choi
Changick Kim
75
302
0
14 May 2019
Exploring Object Relation in Mean Teacher for Cross-Domain Detection
Exploring Object Relation in Mean Teacher for Cross-Domain Detection
Qi Cai
Yingwei Pan
Chong-Wah Ngo
Xinmei Tian
Ling-yu Duan
Ting Yao
ViTOOD
89
308
0
25 Apr 2019
Automatic adaptation of object detectors to new domains using
  self-training
Automatic adaptation of object detectors to new domains using self-training
Aruni RoyChowdhury
Prithvijit Chakrabarty
Ashish Singh
SouYoung Jin
Huaizu Jiang
Liangliang Cao
Erik Learned-Miller
VLMObjD
87
165
0
15 Apr 2019
Towards Universal Object Detection by Domain Attention
Towards Universal Object Detection by Domain Attention
Xudong Wang
Zhaowei Cai
Dashan Gao
Nuno Vasconcelos
OOD
113
198
0
09 Apr 2019
A Robust Learning Approach to Domain Adaptive Object Detection
A Robust Learning Approach to Domain Adaptive Object Detection
Mehran Khodabandeh
Arash Vahdat
Mani Ranjbar
W. Macready
ObjDOODTTA
77
246
0
04 Apr 2019
FCOS: Fully Convolutional One-Stage Object Detection
FCOS: Fully Convolutional One-Stage Object Detection
Zhi Tian
Chunhua Shen
Hao Chen
Tong He
ObjD
154
5,018
0
02 Apr 2019
ScratchDet: Training Single-Shot Object Detectors from Scratch
ScratchDet: Training Single-Shot Object Detectors from Scratch
Rui Zhu
Shifeng Zhang
Xiaobo Wang
Longyin Wen
Hailin Shi
Liefeng Bo
Tao Mei
ObjD
112
125
0
19 Oct 2018
The EuroCity Persons Dataset: A Novel Benchmark for Object Detection
The EuroCity Persons Dataset: A Novel Benchmark for Object Detection
Markus Braun
Sebastian Krebs
F. Flohr
D. Gavrila
ObjD
86
230
0
18 May 2018
Cross-Domain Weakly-Supervised Object Detection through Progressive
  Domain Adaptation
Cross-Domain Weakly-Supervised Object Detection through Progressive Domain Adaptation
Naoto Inoue
Ryosuke Furuta
T. Yamasaki
Kiyoharu Aizawa
ObjD
96
532
0
30 Mar 2018
Domain Adaptive Faster R-CNN for Object Detection in the Wild
Domain Adaptive Faster R-CNN for Object Detection in the Wild
Yuhua Chen
Wen Li
Daniel Gehrig
Dengxin Dai
Luc Van Gool
OODObjD
115
1,305
0
08 Mar 2018
Learning to Adapt Structured Output Space for Semantic Segmentation
Learning to Adapt Structured Output Space for Semantic Segmentation
Yi-Hsuan Tsai
Wei-Chih Hung
S. Schulter
Kihyuk Sohn
Ming-Hsuan Yang
Manmohan Chandraker
OODSSeg
160
1,550
0
28 Feb 2018
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman
Eric Tzeng
Taesung Park
Jun-Yan Zhu
Phillip Isola
Kate Saenko
Alexei A. Efros
Trevor Darrell
151
3,009
0
08 Nov 2017
mixup: Beyond Empirical Risk Minimization
mixup: Beyond Empirical Risk Minimization
Hongyi Zhang
Moustapha Cissé
Yann N. Dauphin
David Lopez-Paz
NoLa
318
9,815
0
25 Oct 2017
Semantic Foggy Scene Understanding with Synthetic Data
Semantic Foggy Scene Understanding with Synthetic Data
Daniel Gehrig
Dengxin Dai
Luc Van Gool
125
1,113
0
25 Aug 2017
Adversarial Discriminative Domain Adaptation
Adversarial Discriminative Domain Adaptation
Eric Tzeng
Judy Hoffman
Kate Saenko
Trevor Darrell
GANOOD
284
4,680
0
17 Feb 2017
YOLO9000: Better, Faster, Stronger
YOLO9000: Better, Faster, Stronger
Joseph Redmon
Ali Farhadi
VLMObjD
183
15,660
0
25 Dec 2016
Driving in the Matrix: Can Virtual Worlds Replace Human-Generated
  Annotations for Real World Tasks?
Driving in the Matrix: Can Virtual Worlds Replace Human-Generated Annotations for Real World Tasks?
Matthew Johnson-Roberson
Charlie Barto
Rounak Mehta
S. N. Sridhar
Karl Rosaen
Ram Vasudevan
127
620
0
06 Oct 2016
The Cityscapes Dataset for Semantic Urban Scene Understanding
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts
Mohamed Omran
Sebastian Ramos
Timo Rehfeld
Markus Enzweiler
Rodrigo Benenson
Uwe Franke
Stefan Roth
Bernt Schiele
1.1K
11,664
0
06 Apr 2016
Simultaneous Deep Transfer Across Domains and Tasks
Simultaneous Deep Transfer Across Domains and Tasks
Eric Tzeng
Judy Hoffman
Trevor Darrell
Kate Saenko
OOD
93
1,373
0
08 Oct 2015
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GANOOD
411
9,527
0
28 May 2015
Learning Transferable Features with Deep Adaptation Networks
Learning Transferable Features with Deep Adaptation Networks
Mingsheng Long
Yue Cao
Jianmin Wang
Michael I. Jordan
OOD
233
5,215
0
10 Feb 2015
How transferable are features in deep neural networks?
How transferable are features in deep neural networks?
J. Yosinski
Jeff Clune
Yoshua Bengio
Hod Lipson
OOD
238
8,363
0
06 Nov 2014
Unsupervised Domain Adaptation by Backpropagation
Unsupervised Domain Adaptation by Backpropagation
Yaroslav Ganin
Victor Lempitsky
OOD
258
6,048
0
26 Sep 2014
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