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Robust Image Completion via Deep Feature Transformations

Jianmin Jiang, Hossam M. Kasem, Kwok-Wai Hung
2019 IEEE Access  
In this paper, we propose a novel robust missing information reconstruction framework via deep feature transformations to simultaneously address both geometric corrections and image completion.  ...  INDEX TERMS Deep feature transformation, geometric transformation, image completion.  ...  Fig.3 illustrates the overall structure of the proposed robust image completion framework, named as deep feature transformation framework.  ... 
doi:10.1109/access.2019.2935130 fatcat:be3w77l6sres3iebeqguxri2fa

VCIP 2020 Index

2020 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)  
Improving Robustness of DNNs against Comm Corruptions via Gaussian Adversarial Training Wan, Zekang Deep Convolutional Neural Network Based on Multi-Scale Feature Extraction for Image Denoising  ...  w Blurred Reflectance Li, Haoliang Improving Robustness of DNNs against Comm Corruptions via Gaussian Adversarial Training Li, Hengxin Lightweight Color Image Demosaicking with Multi-Core Feature  ... 
doi:10.1109/vcip49819.2020.9301896 fatcat:bdh7cuvstzgrbaztnahjdp5s5y

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 1299-1312 Deep Portrait Image Completion and Extrapolation. Wu, X., +, TIP 2020 2344-2355 Deep Spatial Transformation for Pose-Guided Person Image Generation and Animation.  ...  Zhang, J., +, TIP 2020 72-84 Few-Shot Text Style Transfer via Deep Feature Similarity.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Deep Learning for Remote Sensing Image Understanding

Liangpei Zhang, Gui-Song Xia, Tianfu Wu, Liang Lin, Xue Cheng Tai
2016 Journal of Sensors  
In addition, deep learning approaches make better use of big data and provide an end-to-end learning framework in which jointly learning feature transformations and classifiers via the back propagation  ...  These highlevel feature representations are more powerful and robust in typical visual tasks.  ...  In addition, deep learning approaches make better use of big data and provide an end-to-end learning framework in which jointly learning feature transformations and classifiers via the back propagation  ... 
doi:10.1155/2016/7954154 fatcat:yoyzkgdi25er5hqggp4qub7plu

2019 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 29

2019 IEEE transactions on circuits and systems for video technology (Print)  
., +, TCSVT Nov. 2019 3173-3183 SSDH: Semi-Supervised Deep Hashing for Large Scale Image Retrieval. Multi-Grained Deep Feature Learning for Robust Pedestrian Detection.  ...  Fast Single-Image Super-Resolution via Deep Network With Component Learning. Xie, C., +, TCSVT Dec. 2019 3473-3486 Hadamard Transform-Based Optimized HEVC Video Coding.  ... 
doi:10.1109/tcsvt.2019.2959179 fatcat:2bdmsygnonfjnmnvmb72c63tja

A high-precision underwater object detection based on joint self-supervised deblurring and improved spatial transformer network [article]

Xiuyuan Li, Fengchao Li, Jiangang Yu, Guowen An
2022 arXiv   pre-print
Deep learning-based underwater object detection (UOD) remains a major challenge due to the degraded visibility and difficulty to obtain sufficient underwater object images captured from various perspectives  ...  Aiming at alleviating the limitation of insufficient photos from different perspectives, an improved spatial transformer network is designed based on perspective transformation, adaptively enriching image  ...  Furthermore, a single-shot feature aggregation deep network for UOD was proposed in [35] via introducing multiscale features and complementary context information.  ... 
arXiv:2203.04822v1 fatcat:6ry3lpxd5jbj5l4l2vy3bb3wdm

2021 Index IEEE Transactions on Image Processing Vol. 30

2021 IEEE Transactions on Image Processing  
Wang, J., +, TIP 2021 8580-8594 Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.  ...  Wang, Y., +, TIP 2021 3167-3178 Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging.  ... 
doi:10.1109/tip.2022.3142569 fatcat:z26yhwuecbgrnb2czhwjlf73qu

2021 Index IEEE Signal Processing Letters Vol. 28

2021 IEEE Signal Processing Letters  
Cai, H., +, LSP 2021 404-408 Order Estimation via Matrix Completion for Multi-Switch Antenna Selec-tion.  ...  Raninen, E., +, LSP 2021 2092-2096 Order Estimation via Matrix Completion for Multi-Switch Antenna Selection.  ...  + Check author entry for coauthors H Handwriting recognition Handwritten Text Generation via Disentangled Representations.  ... 
doi:10.1109/lsp.2022.3145253 fatcat:a3xqvok75vgepcckwnhh2mty74

Screen-Shooting Resilient Watermarking Scheme via Learned Invariant Keypoints and QT

Li Li, Rui Bai, Shanqing Zhang, Chin-Chen Chang, Mengtao Shi
2021 Sensors  
This paper proposes a screen-shooting resilient watermarking scheme via learned invariant keypoints and QT; that is, if the watermarked image is displayed on the screen and captured by a camera, the watermark  ...  In our case, we embedded watermarks by combining the feature region filtering model to SuperPoint (FRFS) neural networks, quaternion discrete Fourier transform (QDFT), and tensor decomposition (TD).  ...  transform SURF Speeded up robust features BRISK Binary robust invariant scalable keypoints FAST Features from accelerated segment test BRIEF Binary robust independent elementary features ORB  ... 
doi:10.3390/s21196554 pmid:34640870 pmcid:PMC8512442 fatcat:vfx5qwugxrgspgxmw6rpes6g5u

Table of Contents

2021 IEEE Signal Processing Letters  
Li A Deep Feature Fusion Network Based on Multiple Attention Mechanisms for Joint Iris-Periocular Biometric Recognition .Zhu Difference Value Network for Image Super-Resolution . . . . . . . . . . . .  ...  Liu Statistical Classification via Robust Hypothesis Testing: Non-Asymptotic and Simple Bounds . . . . . . . . . . . . . . . . H.  ... 
doi:10.1109/lsp.2021.3134551 fatcat:ab4b4tb5rrcu5cq6aifdekrizq

Table of contents

2020 IEEE Transactions on Image Processing  
Guan 3805 Graininess-Aware Deep Feature Learning for Robust Pedestrian Detection ..... C. Lin, J. Lu, G. Wang, and J.  ...  Dong 4099 Quasi Fourier-Mellin Transform for Affine Invariant Features .... J.  ... 
doi:10.1109/tip.2019.2940372 fatcat:h23ul2rqazbstcho46uv3lunku

2021 Index IEEE Transactions on Multimedia Vol. 23

2021 IEEE transactions on multimedia  
Yang, Q., +, TMM 2021 3877-3891 Recurrent Generative Adversarial Network for Face Completion. Wang, Q., +, TMM 2021 429-442 Robust Coding of Encrypted Images via 2D Compressed Sensing.  ...  ., +, TMM 2021 1516-1529 Robust Coding of Encrypted Images via 2D Compressed Sensing.  ...  Liao, J., and Kwong, S., Semantic Example Guided Image-to-Image Translation; TMM 2021 1654-1665 Huang, J., see Gong, X., TMM 2021 2820-2832 Huang, J., see Zhong, H., TMM 2021 1264 -1273 Huang, K., see  ... 
doi:10.1109/tmm.2022.3141947 fatcat:lil2nf3vd5ehbfgtslulu7y3lq

Table of contents

2018 IEEE Transactions on Image Processing  
Paull 3036 Region, Boundary, and Shape Analysis Deep Spatiality: Unsupervised Learning of Spatially-Enhanced Global and Local 3D Features by Deep Neural Network With Coupled Softmax ...................  ...  Truong 2762 Structure-Revealing Low-Light Image Enhancement Via Robust Retinex Model ........................................... ........................................................................  ... 
doi:10.1109/tip.2018.2826279 fatcat:g2phh6es3vhq5arrsk62bblzua

A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes [article]

Mazda Moayeri, Phillip Pope, Yogesh Balaji, Soheil Feizi
2022 arXiv   pre-print
Finally, we quantitatively study the attribution problem for neural features by comparing feature saliency with ground-truth localization of semantic attributes.  ...  While datasets with single-label supervision have propelled rapid advances in image classification, additional annotations are necessary in order to quantitatively assess how models make predictions.  ...  Additional examples of spurious features used by a Robust ResNet50 observed via sorting images by saliency alignment (∆ Densities). Misclassifications are in red text.  ... 
arXiv:2201.10766v1 fatcat:hnfnj5h2ive33mbwwc4gkkwq6y

Saccade Mechanisms for Image Classification, Object Detection and Tracking [article]

Saurabh Farkya, Zachary Daniels, Aswin Nadamuni Raghavan, David Zhang, Michael Piacentino
2022 arXiv   pre-print
We conduct experiments by analyzing: i) the robustness of different deep neural network (DNN) feature extractors to partially-sensed images for image classification and object detection, and ii) the utility  ...  of saccades in masking image patches for image classification and object tracking.  ...  We aim to validate the following hypotheses: i) Self-attentionbased transformers [12] are robust to partially-sensed patchbased inputs, and ii) Mimicking saccadic motions captured via human eye-fixation  ... 
arXiv:2206.05102v1 fatcat:4az4xeofpzh2tjlcx4fjkgdk44
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