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Deep Neural Networks are Easily Fooled: High Confidence Predictions for
  Unrecognizable Images
v1v2v3v4 (latest)

Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images

Computer Vision and Pattern Recognition (CVPR), 2014
5 December 2014
Anh Totti Nguyen
J. Yosinski
Jeff Clune
    AAML
ArXiv (abs)PDFHTML

Papers citing "Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images"

50 / 1,455 papers shown
Anti-aliasing Deep Image Classifiers using Novel Depth Adaptive Blurring
  and Activation Function
Anti-aliasing Deep Image Classifiers using Novel Depth Adaptive Blurring and Activation Function
Md Tahmid Hossain
S. Teng
Ferdous Sohel
Guojun Lu
165
18
0
03 Oct 2021
On the Importance of Gradients for Detecting Distributional Shifts in
  the Wild
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
Rui Huang
Andrew Geng
Shouqing Yang
677
418
0
01 Oct 2021
Learning to Predict Trustworthiness with Steep Slope Loss
Learning to Predict Trustworthiness with Steep Slope Loss
Yan Luo
Yongkang Wong
Mohan S. Kankanhalli
Qi Zhao
206
13
0
30 Sep 2021
Can multi-label classification networks know what they don't know?
Can multi-label classification networks know what they don't know?
Haoran Wang
Weitang Liu
Alex E. Bocchieri
Shouqing Yang
OODD
354
127
0
29 Sep 2021
A novel network training approach for open set image recognition
A novel network training approach for open set image recognition
Md Tahmid Hossaina
S. Teng
Guojun Lu
Ferdous Sohel
127
0
0
27 Sep 2021
Two Souls in an Adversarial Image: Towards Universal Adversarial Example
  Detection using Multi-view Inconsistency
Two Souls in an Adversarial Image: Towards Universal Adversarial Example Detection using Multi-view InconsistencyAsia-Pacific Computer Systems Architecture Conference (ACSA), 2021
Sohaib Kiani
S. Awan
Chao Lan
Fengjun Li
Bo Luo
GANAAML
161
11
0
25 Sep 2021
Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual
  Patterns
Targeted Attack on Deep RL-based Autonomous Driving with Learned Visual Patterns
Prasanth Buddareddygari
Travis Zhang
Yezhou Yang
Yi Ren
AAML
175
21
0
16 Sep 2021
The State of the Art when using GPUs in Devising Image Generation
  Methods Using Deep Learning
The State of the Art when using GPUs in Devising Image Generation Methods Using Deep Learning
Yasuko Kawahata
179
0
0
13 Sep 2021
On the Impact of Spurious Correlation for Out-of-distribution Detection
On the Impact of Spurious Correlation for Out-of-distribution Detection
Yifei Ming
Hang Yin
Shouqing Yang
OODD
369
75
0
12 Sep 2021
No True State-of-the-Art? OOD Detection Methods are Inconsistent across
  Datasets
No True State-of-the-Art? OOD Detection Methods are Inconsistent across Datasets
Fahim Tajwar
Ananya Kumar
Sang Michael Xie
Abigail Z. Jacobs
OODD
223
32
0
12 Sep 2021
Detecting and Mitigating Test-time Failure Risks via Model-agnostic
  Uncertainty Learning
Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty LearningIndustrial Conference on Data Mining (IDM), 2021
Preethi Lahoti
Krishna P. Gummadi
Gerhard Weikum
151
4
0
09 Sep 2021
IFBiD: Inference-Free Bias Detection
IFBiD: Inference-Free Bias Detection
Ignacio Serna
Daniel DeAlcala
Aythami Morales
Julian Fierrez
J. Ortega-Garcia
CVBM
175
14
0
09 Sep 2021
Training Deep Networks from Zero to Hero: avoiding pitfalls and going
  beyond
Training Deep Networks from Zero to Hero: avoiding pitfalls and going beyondSIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), 2021
M. Ponti
Fernando Pereira dos Santos
Leo Sampaio Ferraz Ribeiro
G. B. Cavallari
162
18
0
06 Sep 2021
Spatio-Temporal Perturbations for Video Attribution
Spatio-Temporal Perturbations for Video Attribution
Zhenqiang Li
Weimin Wang
Zuoyue Li
Yifei Huang
Yoichi Sato
130
8
0
01 Sep 2021
DomiKnowS: A Library for Integration of Symbolic Domain Knowledge in
  Deep Learning
DomiKnowS: A Library for Integration of Symbolic Domain Knowledge in Deep LearningConference on Empirical Methods in Natural Language Processing (EMNLP), 2021
Hossein Rajaby Faghihi
Quan Guo
Andrzej Uszok
Aliakbar Nafar
Elaheh Raisi
Parisa Kordjamshidi
AI4CE
164
21
0
27 Aug 2021
Revealing the Distributional Vulnerability of Discriminators by Implicit
  Generators
Revealing the Distributional Vulnerability of Discriminators by Implicit GeneratorsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021
Zhilin Zhao
LongBing Cao
Kun-Yu Lin
441
17
0
23 Aug 2021
Learning-to-learn non-convex piecewise-Lipschitz functions
Learning-to-learn non-convex piecewise-Lipschitz functions
Maria-Florina Balcan
M. Khodak
Dravyansh Sharma
Ameet Talwalkar
152
19
0
19 Aug 2021
A Survey on Open Set Recognition
A Survey on Open Set Recognition
Atefeh Mahdavi
Marco M. Carvalho
BDL
153
44
0
18 Aug 2021
A Sparse Coding Interpretation of Neural Networks and Theoretical
  Implications
A Sparse Coding Interpretation of Neural Networks and Theoretical Implications
Joshua Bowren
FAtt
217
1
0
14 Aug 2021
Optical Adversarial Attack
Optical Adversarial Attack
Abhiram Gnanasambandam
A. Sherman
Stanley H. Chan
AAML
280
79
0
13 Aug 2021
CODEs: Chamfer Out-of-Distribution Examples against Overconfidence Issue
CODEs: Chamfer Out-of-Distribution Examples against Overconfidence IssueIEEE International Conference on Computer Vision (ICCV), 2021
Keke Tang
Dingruibo Miao
Weilong Peng
Jianpeng Wu
Yawen Shi
Zhaoquan Gu
Zhihong Tian
Wenping Wang
OODD
331
34
0
13 Aug 2021
Existence, Stability and Scalability of Orthogonal Convolutional Neural
  Networks
Existence, Stability and Scalability of Orthogonal Convolutional Neural NetworksJournal of machine learning research (JMLR), 2021
El Mehdi Achour
Franccois Malgouyres
Franck Mamalet
327
22
0
12 Aug 2021
WideCaps: A Wide Attention based Capsule Network for Image
  Classification
WideCaps: A Wide Attention based Capsule Network for Image Classification
Pawan S. Jogi
R. Sharma
Hemantha Reddy
M. Vani
Jeny Rajan
244
1
0
08 Aug 2021
Monte Carlo DropBlock for Modelling Uncertainty in Object Detection
Monte Carlo DropBlock for Modelling Uncertainty in Object DetectionPattern Recognition (Pattern Recogn.), 2021
K. Deepshikha
Sai Harsha Yelleni
P. K. Srijith
C.Krishna Mohan
BDLUQCV
159
109
0
08 Aug 2021
Triggering Failures: Out-Of-Distribution detection by learning from
  local adversarial attacks in Semantic Segmentation
Triggering Failures: Out-Of-Distribution detection by learning from local adversarial attacks in Semantic Segmentation
Victor Besnier
Andrei Bursuc
David Picard
Alexandre Briot
UQCV
240
54
0
03 Aug 2021
Robust Semantic Segmentation with Superpixel-Mix
Robust Semantic Segmentation with Superpixel-Mix
Gianni Franchi
Nacim Belkhir
Mai Lan Ha
Yufei Hu
Andrei Bursuc
V. Blanz
Angela Yao
UQCV
220
24
0
02 Aug 2021
Structure and Performance of Fully Connected Neural Networks: Emerging
  Complex Network Properties
Structure and Performance of Fully Connected Neural Networks: Emerging Complex Network Properties
Leonardo F. S. Scabini
Odemir M. Bruno
GNN
111
79
0
29 Jul 2021
Resisting Out-of-Distribution Data Problem in Perturbation of XAI
Resisting Out-of-Distribution Data Problem in Perturbation of XAI
Luyu Qiu
Yi Yang
Caleb Chen Cao
Jing Liu
Yueyuan Zheng
H. Ngai
J. H. Hsiao
Lei Chen
236
19
0
27 Jul 2021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Energy-Based Open-World Uncertainty Modeling for Confidence CalibrationIEEE International Conference on Computer Vision (ICCV), 2021
Yezhen Wang
Yue Liu
Tong Che
Kaiyang Zhou
Ziwei Liu
Dongsheng Li
UQCV
287
66
0
27 Jul 2021
Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated
  Failure Time Models
Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time ModelsMachine Learning in Health Care (MLHC), 2021
Zhiliang Wu
Yinchong Yang
Peter A. Fasching
Volker Tresp
BDL
119
11
0
26 Jul 2021
Improving Variational Autoencoder based Out-of-Distribution Detection
  for Embedded Real-time Applications
Improving Variational Autoencoder based Out-of-Distribution Detection for Embedded Real-time ApplicationsACM Transactions on Embedded Computing Systems (TECS), 2021
Yeli Feng
Daniel Jun Xian Ng
Arvind Easwaran
OODD
179
21
0
25 Jul 2021
An Uncertainty-Aware Deep Learning Framework for Defect Detection in
  Casting Products
An Uncertainty-Aware Deep Learning Framework for Defect Detection in Casting ProductsSocial Science Research Network (SSRN), 2021
Maryam Habibpour
Hassan Gharoun
AmirReza Tajally
Afshar Shamsi Jokandan
Hamzeh Asgharnezhad
Abbas Khosravi
S. Nahavandi
UQCV
197
19
0
24 Jul 2021
CogSense: A Cognitively Inspired Framework for Perception Adaptation
CogSense: A Cognitively Inspired Framework for Perception Adaptation
Hyukseong Kwon
Amir M. Rahimi
Kevin G. Lee
Amit Agarwal
Rajan Bhattacharyya
74
0
0
22 Jul 2021
A Survey of Uncertainty in Deep Neural Networks
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDLUQCVOOD
557
1,496
0
07 Jul 2021
Rethinking Positional Encoding
Rethinking Positional Encoding
Jianqiao Zheng
Sameera Ramasinghe
Simon Lucey
230
62
0
06 Jul 2021
Dealing with Adversarial Player Strategies in the Neural Network Game
  iNNk through Ensemble Learning
Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning
Mathias Löwe
Jennifer Villareale
Evan Freed
Aleksanteri Sladek
Jichen Zhu
S. Risi
AAML
226
5
0
05 Jul 2021
Pool of Experts: Realtime Querying Specialized Knowledge in Massive
  Neural Networks
Pool of Experts: Realtime Querying Specialized Knowledge in Massive Neural Networks
Hakbin Kim
Dong-Wan Choi
128
2
0
03 Jul 2021
Backward-Compatible Prediction Updates: A Probabilistic Approach
Backward-Compatible Prediction Updates: A Probabilistic Approach
Frederik Trauble
Julius von Kügelgen
Matthäus Kleindessner
Francesco Locatello
Bernhard Schölkopf
Peter V. Gehler
271
17
0
02 Jul 2021
Local Reweighting for Adversarial Training
Local Reweighting for Adversarial Training
Ruize Gao
Yifan Zhang
Kaiwen Zhou
Gang Niu
Bo Han
James Cheng
AAMLOOD
100
6
0
30 Jun 2021
CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image
  Encoders
CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image EncodersNeural Information Processing Systems (NeurIPS), 2021
Kevin Frans
Lisa Soros
Olaf Witkowski
CLIP
224
265
0
28 Jun 2021
Inverting and Understanding Object Detectors
Inverting and Understanding Object Detectors
Ang Cao
Justin Johnson
ObjD
201
3
0
26 Jun 2021
EARLIN: Early Out-of-Distribution Detection for Resource-efficient
  Collaborative Inference
EARLIN: Early Out-of-Distribution Detection for Resource-efficient Collaborative Inference
Sumaiya Tabassum Nimi
Md. Adnan Arefeen
M. Y. S. Uddin
Yugyung Lee
OODDFedML
187
1
0
25 Jun 2021
How Well do Feature Visualizations Support Causal Understanding of CNN
  Activations?
How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
Roland S. Zimmermann
Judy Borowski
Robert Geirhos
Matthias Bethge
Thomas S. A. Wallis
Wieland Brendel
FAtt
321
39
0
23 Jun 2021
Adversarial Training Helps Transfer Learning via Better Representations
Adversarial Training Helps Transfer Learning via Better RepresentationsNeural Information Processing Systems (NeurIPS), 2021
Zhun Deng
Linjun Zhang
Kailas Vodrahalli
Kenji Kawaguchi
James Zou
GAN
186
58
0
18 Jun 2021
Being a Bit Frequentist Improves Bayesian Neural Networks
Being a Bit Frequentist Improves Bayesian Neural NetworksInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Agustinus Kristiadi
Matthias Hein
Philipp Hennig
BDLUQCV
227
17
0
18 Jun 2021
Gradual Domain Adaptation via Self-Training of Auxiliary Models
Gradual Domain Adaptation via Self-Training of Auxiliary Models
Yabin Zhang
Bin Deng
Kui Jia
Lei Zhang
CLL
210
13
0
18 Jun 2021
Explainable AI for Natural Adversarial Images
Explainable AI for Natural Adversarial Images
Tomas Folke
Zhaobin Li
Ravi B. Sojitra
Scott Cheng-Hsin Yang
Patrick Shafto
AAMLFAtt
111
4
0
16 Jun 2021
Robust Out-of-Distribution Detection on Deep Probabilistic Generative
  Models
Robust Out-of-Distribution Detection on Deep Probabilistic Generative Models
Jaemoo Choi
Changyeon Yoon
Jeongwoo Bae
Myung-joo Kang
OODD
207
4
0
15 Jun 2021
Scale-invariant scale-channel networks: Deep networks that generalise to
  previously unseen scales
Scale-invariant scale-channel networks: Deep networks that generalise to previously unseen scalesJournal of Mathematical Imaging and Vision (JMIV), 2021
Ylva Jansson
T. Lindeberg
209
27
0
11 Jun 2021
Sparse and Imperceptible Adversarial Attack via a Homotopy Algorithm
Sparse and Imperceptible Adversarial Attack via a Homotopy AlgorithmInternational Conference on Machine Learning (ICML), 2021
Mingkang Zhu
Tianlong Chen
Zinan Lin
AAML
137
28
0
10 Jun 2021
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