Sorry, you need to enable JavaScript to visit this website.

ICIP 2019

The International Conference on Image Processing (ICIP), sponsored by the IEEE Signal Processing Society, is the premier forum for the presentation of technological advances and research results in the fields of theoretical, experimental, and applied image and video processing. ICIP has been held annually since 1994, brings together leading engineers and scientists in image and video processing from around the world. Visit website.

From Mapping to Localization: A Complete Framework to Visually Estimate Position and Attitude for Autonomous Vehicles


Autonomous vehicle framework relies on localization algorithms to position itself and navigates to the destination. In this paper, we explore a light-weight visual localization method to realize the vehicle position and attitude estimation based on images rather than the dominant LIDAR data. We apply SLAM and an offline map correction method to generate a high precision map, which composes 3D points and feature descriptors. For each image, we extract the features and match against the map to explore correspondences.

Paper Details

Authors:
Xue-Iuan Wong, James McBride
Submitted On:
22 September 2019 - 12:32am
Short Link:
Type:
Event:
Document Year:
Cite

Document Files

icip3500.pdf

(18)

Subscribe

[1] Xue-Iuan Wong, James McBride, "From Mapping to Localization: A Complete Framework to Visually Estimate Position and Attitude for Autonomous Vehicles", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4812. Accessed: Jan. 26, 2020.
@article{4812-19,
url = {http://sigport.org/4812},
author = {Xue-Iuan Wong; James McBride },
publisher = {IEEE SigPort},
title = {From Mapping to Localization: A Complete Framework to Visually Estimate Position and Attitude for Autonomous Vehicles},
year = {2019} }
TY - EJOUR
T1 - From Mapping to Localization: A Complete Framework to Visually Estimate Position and Attitude for Autonomous Vehicles
AU - Xue-Iuan Wong; James McBride
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4812
ER -
Xue-Iuan Wong, James McBride. (2019). From Mapping to Localization: A Complete Framework to Visually Estimate Position and Attitude for Autonomous Vehicles. IEEE SigPort. http://sigport.org/4812
Xue-Iuan Wong, James McBride, 2019. From Mapping to Localization: A Complete Framework to Visually Estimate Position and Attitude for Autonomous Vehicles. Available at: http://sigport.org/4812.
Xue-Iuan Wong, James McBride. (2019). "From Mapping to Localization: A Complete Framework to Visually Estimate Position and Attitude for Autonomous Vehicles." Web.
1. Xue-Iuan Wong, James McBride. From Mapping to Localization: A Complete Framework to Visually Estimate Position and Attitude for Autonomous Vehicles [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4812

AN IMAGE IDENTIFICATION SCHEME OF ENCRYPTED JPEG IMAGES FOR PRIVACY PRESERVING PHOTO SHARING SERVICES

Paper Details

Authors:
Kenta Iida, Hitoshi Kiya
Submitted On:
29 September 2019 - 5:53am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICIP2019poster_KIida_final.pdf

(20)

Subscribe

[1] Kenta Iida, Hitoshi Kiya, "AN IMAGE IDENTIFICATION SCHEME OF ENCRYPTED JPEG IMAGES FOR PRIVACY PRESERVING PHOTO SHARING SERVICES", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4811. Accessed: Jan. 26, 2020.
@article{4811-19,
url = {http://sigport.org/4811},
author = {Kenta Iida; Hitoshi Kiya },
publisher = {IEEE SigPort},
title = {AN IMAGE IDENTIFICATION SCHEME OF ENCRYPTED JPEG IMAGES FOR PRIVACY PRESERVING PHOTO SHARING SERVICES},
year = {2019} }
TY - EJOUR
T1 - AN IMAGE IDENTIFICATION SCHEME OF ENCRYPTED JPEG IMAGES FOR PRIVACY PRESERVING PHOTO SHARING SERVICES
AU - Kenta Iida; Hitoshi Kiya
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4811
ER -
Kenta Iida, Hitoshi Kiya. (2019). AN IMAGE IDENTIFICATION SCHEME OF ENCRYPTED JPEG IMAGES FOR PRIVACY PRESERVING PHOTO SHARING SERVICES. IEEE SigPort. http://sigport.org/4811
Kenta Iida, Hitoshi Kiya, 2019. AN IMAGE IDENTIFICATION SCHEME OF ENCRYPTED JPEG IMAGES FOR PRIVACY PRESERVING PHOTO SHARING SERVICES. Available at: http://sigport.org/4811.
Kenta Iida, Hitoshi Kiya. (2019). "AN IMAGE IDENTIFICATION SCHEME OF ENCRYPTED JPEG IMAGES FOR PRIVACY PRESERVING PHOTO SHARING SERVICES." Web.
1. Kenta Iida, Hitoshi Kiya. AN IMAGE IDENTIFICATION SCHEME OF ENCRYPTED JPEG IMAGES FOR PRIVACY PRESERVING PHOTO SHARING SERVICES [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4811

Towards Unified Aesthetics and Emotion Prediction in Images

Paper Details

Authors:
Submitted On:
21 September 2019 - 9:47am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Towards Unified Aesthetics and Emotion Prediction in Images

(39)

Subscribe

[1] , "Towards Unified Aesthetics and Emotion Prediction in Images", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4810. Accessed: Jan. 26, 2020.
@article{4810-19,
url = {http://sigport.org/4810},
author = { },
publisher = {IEEE SigPort},
title = {Towards Unified Aesthetics and Emotion Prediction in Images},
year = {2019} }
TY - EJOUR
T1 - Towards Unified Aesthetics and Emotion Prediction in Images
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4810
ER -
. (2019). Towards Unified Aesthetics and Emotion Prediction in Images. IEEE SigPort. http://sigport.org/4810
, 2019. Towards Unified Aesthetics and Emotion Prediction in Images. Available at: http://sigport.org/4810.
. (2019). "Towards Unified Aesthetics and Emotion Prediction in Images." Web.
1. . Towards Unified Aesthetics and Emotion Prediction in Images [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4810

Learning The Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks

Paper Details

Authors:
Submitted On:
21 September 2019 - 9:43am
Short Link:
Type:
Event:

Document Files

icip2019-poster-haoliang-WQ.PD_.5.pdf

(32)

Subscribe

[1] , "Learning The Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4809. Accessed: Jan. 26, 2020.
@article{4809-19,
url = {http://sigport.org/4809},
author = { },
publisher = {IEEE SigPort},
title = {Learning The Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks},
year = {2019} }
TY - EJOUR
T1 - Learning The Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4809
ER -
. (2019). Learning The Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks. IEEE SigPort. http://sigport.org/4809
, 2019. Learning The Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks. Available at: http://sigport.org/4809.
. (2019). "Learning The Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks." Web.
1. . Learning The Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4809

VARIABLE-LENGTH QUANTIZATION STRATEGY FOR HASHING

Paper Details

Authors:
Submitted On:
21 September 2019 - 9:49am
Short Link:
Type:
Event:
Paper Code:
Document Year:
Cite

Document Files

VLQ.pptx

(28)

Subscribe

[1] , "VARIABLE-LENGTH QUANTIZATION STRATEGY FOR HASHING", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4808. Accessed: Jan. 26, 2020.
@article{4808-19,
url = {http://sigport.org/4808},
author = { },
publisher = {IEEE SigPort},
title = {VARIABLE-LENGTH QUANTIZATION STRATEGY FOR HASHING},
year = {2019} }
TY - EJOUR
T1 - VARIABLE-LENGTH QUANTIZATION STRATEGY FOR HASHING
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4808
ER -
. (2019). VARIABLE-LENGTH QUANTIZATION STRATEGY FOR HASHING. IEEE SigPort. http://sigport.org/4808
, 2019. VARIABLE-LENGTH QUANTIZATION STRATEGY FOR HASHING. Available at: http://sigport.org/4808.
. (2019). "VARIABLE-LENGTH QUANTIZATION STRATEGY FOR HASHING." Web.
1. . VARIABLE-LENGTH QUANTIZATION STRATEGY FOR HASHING [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4808

A UNIFIED UNSUPERVISED LEARNING FRAMEWORK FOR STEREO MATCHING AND EGO-MOTION ESTIMATION

Paper Details

Authors:
Submitted On:
21 September 2019 - 8:52am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

A UNIFIED UNSUPERVISED LEARNING FRAMEWORK FOR STEREO MATCHING AND EGO-MOTION ESTIMATION

(30)

Keywords

Additional Categories

Subscribe

[1] , "A UNIFIED UNSUPERVISED LEARNING FRAMEWORK FOR STEREO MATCHING AND EGO-MOTION ESTIMATION", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4807. Accessed: Jan. 26, 2020.
@article{4807-19,
url = {http://sigport.org/4807},
author = { },
publisher = {IEEE SigPort},
title = {A UNIFIED UNSUPERVISED LEARNING FRAMEWORK FOR STEREO MATCHING AND EGO-MOTION ESTIMATION},
year = {2019} }
TY - EJOUR
T1 - A UNIFIED UNSUPERVISED LEARNING FRAMEWORK FOR STEREO MATCHING AND EGO-MOTION ESTIMATION
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4807
ER -
. (2019). A UNIFIED UNSUPERVISED LEARNING FRAMEWORK FOR STEREO MATCHING AND EGO-MOTION ESTIMATION. IEEE SigPort. http://sigport.org/4807
, 2019. A UNIFIED UNSUPERVISED LEARNING FRAMEWORK FOR STEREO MATCHING AND EGO-MOTION ESTIMATION. Available at: http://sigport.org/4807.
. (2019). "A UNIFIED UNSUPERVISED LEARNING FRAMEWORK FOR STEREO MATCHING AND EGO-MOTION ESTIMATION." Web.
1. . A UNIFIED UNSUPERVISED LEARNING FRAMEWORK FOR STEREO MATCHING AND EGO-MOTION ESTIMATION [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4807

When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks


Discovering and exploiting the causality in deep neural networks (DNNs) are crucial challenges for understanding and reasoning causal effects (CE) on an explainable visual model. "Intervention" has been widely used for recognizing a causal relation ontologically. In this paper, we propose a causal inference framework for visual reasoning via do-calculus. To study the intervention effects on pixel-level features for causal reasoning, we introduce pixel-wise masking and adversarial perturbation.

Paper Details

Authors:
Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen, Yi-Chang James Tsai, Xiaoli Ma
Submitted On:
21 September 2019 - 7:34am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Oral_ICIP_2019_Adversarial_Causality_0927.pdf

(40)

Subscribe

[1] Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen, Yi-Chang James Tsai, Xiaoli Ma, "When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4806. Accessed: Jan. 26, 2020.
@article{4806-19,
url = {http://sigport.org/4806},
author = {Chao-Han Huck Yang; Yi-Chieh Liu; Pin-Yu Chen; Yi-Chang James Tsai; Xiaoli Ma },
publisher = {IEEE SigPort},
title = {When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks},
year = {2019} }
TY - EJOUR
T1 - When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks
AU - Chao-Han Huck Yang; Yi-Chieh Liu; Pin-Yu Chen; Yi-Chang James Tsai; Xiaoli Ma
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4806
ER -
Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen, Yi-Chang James Tsai, Xiaoli Ma. (2019). When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks. IEEE SigPort. http://sigport.org/4806
Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen, Yi-Chang James Tsai, Xiaoli Ma, 2019. When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks. Available at: http://sigport.org/4806.
Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen, Yi-Chang James Tsai, Xiaoli Ma. (2019). "When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks." Web.
1. Chao-Han Huck Yang, Yi-Chieh Liu, Pin-Yu Chen, Yi-Chang James Tsai, Xiaoli Ma. When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4806

RATE-DISTORTION DRIVEN SEPARATION OF DIFFUSE AND SPECULAR COMPONENTS IN MULTIVIEW IMAGERY


In this work we explore an overcomplete representation of
multiview imagery for the purpose of compression. We
present a rate-distortion (R-D) driven approach to decompose
multiview datasets into two additive parts which can
be interpreted as being the diffuse and specular components.
We apply different transforms to each component such that
the compressibility of input data is improved. We describe
a framework which performs the R-D optimized separation
in a registered domain to avoid the complexity of warping

Paper Details

Authors:
Maryam Haghighat, Reji Mathew and David Taubman
Submitted On:
21 September 2019 - 7:18am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

ICIP2019_Haghighat_Poster.pdf

(41)

Subscribe

[1] Maryam Haghighat, Reji Mathew and David Taubman, "RATE-DISTORTION DRIVEN SEPARATION OF DIFFUSE AND SPECULAR COMPONENTS IN MULTIVIEW IMAGERY", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4805. Accessed: Jan. 26, 2020.
@article{4805-19,
url = {http://sigport.org/4805},
author = {Maryam Haghighat; Reji Mathew and David Taubman },
publisher = {IEEE SigPort},
title = {RATE-DISTORTION DRIVEN SEPARATION OF DIFFUSE AND SPECULAR COMPONENTS IN MULTIVIEW IMAGERY},
year = {2019} }
TY - EJOUR
T1 - RATE-DISTORTION DRIVEN SEPARATION OF DIFFUSE AND SPECULAR COMPONENTS IN MULTIVIEW IMAGERY
AU - Maryam Haghighat; Reji Mathew and David Taubman
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4805
ER -
Maryam Haghighat, Reji Mathew and David Taubman. (2019). RATE-DISTORTION DRIVEN SEPARATION OF DIFFUSE AND SPECULAR COMPONENTS IN MULTIVIEW IMAGERY. IEEE SigPort. http://sigport.org/4805
Maryam Haghighat, Reji Mathew and David Taubman, 2019. RATE-DISTORTION DRIVEN SEPARATION OF DIFFUSE AND SPECULAR COMPONENTS IN MULTIVIEW IMAGERY. Available at: http://sigport.org/4805.
Maryam Haghighat, Reji Mathew and David Taubman. (2019). "RATE-DISTORTION DRIVEN SEPARATION OF DIFFUSE AND SPECULAR COMPONENTS IN MULTIVIEW IMAGERY." Web.
1. Maryam Haghighat, Reji Mathew and David Taubman. RATE-DISTORTION DRIVEN SEPARATION OF DIFFUSE AND SPECULAR COMPONENTS IN MULTIVIEW IMAGERY [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4805

Unsupervised Single Image Underwater Depth Estimation


Depth estimation from a single underwater image is one of the most challenging problems and is highly ill-posed. Due to the absence of large generalized underwater depth datasets and the difficulty in obtaining ground truth depth-maps, supervised learning techniques such as direct depth regression cannot be used. In this paper, we propose an unsupervised method for depth estimation from a single underwater image taken "in the wild" by using haze as a cue for depth.

Paper Details

Authors:
Honey Gupta, Kaushik Mitra
Submitted On:
21 September 2019 - 6:32am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

Unsupervised Single Image Underwater Depth Estimation.pdf

(27)

Keywords

Additional Categories

Subscribe

[1] Honey Gupta, Kaushik Mitra, "Unsupervised Single Image Underwater Depth Estimation", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4804. Accessed: Jan. 26, 2020.
@article{4804-19,
url = {http://sigport.org/4804},
author = {Honey Gupta; Kaushik Mitra },
publisher = {IEEE SigPort},
title = {Unsupervised Single Image Underwater Depth Estimation},
year = {2019} }
TY - EJOUR
T1 - Unsupervised Single Image Underwater Depth Estimation
AU - Honey Gupta; Kaushik Mitra
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4804
ER -
Honey Gupta, Kaushik Mitra. (2019). Unsupervised Single Image Underwater Depth Estimation. IEEE SigPort. http://sigport.org/4804
Honey Gupta, Kaushik Mitra, 2019. Unsupervised Single Image Underwater Depth Estimation. Available at: http://sigport.org/4804.
Honey Gupta, Kaushik Mitra. (2019). "Unsupervised Single Image Underwater Depth Estimation." Web.
1. Honey Gupta, Kaushik Mitra. Unsupervised Single Image Underwater Depth Estimation [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4804

REAL-TIME LIGHT FIELD DEPTH ESTIMATION VIA GPU-ACCELERATED MULTI-VIEW SEMI-GLOBAL MATCHING

Paper Details

Authors:
Submitted On:
21 September 2019 - 5:17am
Short Link:
Type:
Event:
Presenter's Name:
Paper Code:
Document Year:
Cite

Document Files

wangyuanqi_poster.pdf

(28)

Subscribe

[1] , "REAL-TIME LIGHT FIELD DEPTH ESTIMATION VIA GPU-ACCELERATED MULTI-VIEW SEMI-GLOBAL MATCHING", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4803. Accessed: Jan. 26, 2020.
@article{4803-19,
url = {http://sigport.org/4803},
author = { },
publisher = {IEEE SigPort},
title = {REAL-TIME LIGHT FIELD DEPTH ESTIMATION VIA GPU-ACCELERATED MULTI-VIEW SEMI-GLOBAL MATCHING},
year = {2019} }
TY - EJOUR
T1 - REAL-TIME LIGHT FIELD DEPTH ESTIMATION VIA GPU-ACCELERATED MULTI-VIEW SEMI-GLOBAL MATCHING
AU -
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4803
ER -
. (2019). REAL-TIME LIGHT FIELD DEPTH ESTIMATION VIA GPU-ACCELERATED MULTI-VIEW SEMI-GLOBAL MATCHING. IEEE SigPort. http://sigport.org/4803
, 2019. REAL-TIME LIGHT FIELD DEPTH ESTIMATION VIA GPU-ACCELERATED MULTI-VIEW SEMI-GLOBAL MATCHING. Available at: http://sigport.org/4803.
. (2019). "REAL-TIME LIGHT FIELD DEPTH ESTIMATION VIA GPU-ACCELERATED MULTI-VIEW SEMI-GLOBAL MATCHING." Web.
1. . REAL-TIME LIGHT FIELD DEPTH ESTIMATION VIA GPU-ACCELERATED MULTI-VIEW SEMI-GLOBAL MATCHING [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4803

Pages