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Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards a Fourier Perspective
2021
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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We perform task-specific and joint analysis and reveal that (a) frequency is a key factor that influences their performance based on the proposed entropy metric for quantifying the frequency distribution ...
We also perform feature layer analysis for providing deep insight on model generalization and robustness. ...
Fourier Transform and Frequency Since a large portion of the analysis in this work is dependent on the understanding of image frequency, here we summarize the main points regarding the Fourier transform ...
doi:10.1609/aaai.v35i4.16441
fatcat:wmlvrs4dmbhypf7clqincqgfne
Implicit Neural Image Stitching
[article]
2024
arXiv
pre-print
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Although the recent learning-based stitchings relax such disparities, the required methods impose sacrifice of image qualities failing to capture high-frequency details for stitched images. ...
Our method estimates Fourier coefficients of images for quality-enhancing warps. ...
Implementation Details Estimation of Alignment We employ a deep homography estimator IHN [4] and robust ELA [21] for estimation of transformation to align images. ...
arXiv:2309.01409v5
fatcat:npzgwecdr5fkpgpofizv74d33u
A generalized divergence measure for robust image registration
2003
IEEE Transactions on Signal Processing
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As the key focus of this paper, we apply Jensen-Rényi divergence for inverse synthetic aperture radar (ISAR) image registration. The goal is to estimate the target motion during the imaging time. ...
Our approach applies Jensen-Rényi divergence to measure the statistical dependence between consecutive ISAR image frames, which would be maximal if the images are geometrically aligned. ...
If the misalignment between and can be modeled by a spatial transformation , then for all , we have JR (13) In case of JR for any probability distribution such that and JR if and only if . ...
doi:10.1109/tsp.2003.810305
fatcat:dl2uctovrvgedookqgsdgeph6m
MultiCorrupt: A Multi-Modal Robustness Dataset and Benchmark of LiDAR-Camera Fusion for 3D Object Detection
[article]
2024
arXiv
pre-print
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2024 pre-print arXiv:2402.11677v2 fatcat:g2gwtnhlj5ak7fmdc3zupc375yOther Versions
Issues such as sensor misalignment, miscalibration, and disparate sampling frequencies lead to spatial and temporal misalignment in data from LiDAR and cameras. ...
Multi-modal 3D object detection models for automated driving have demonstrated exceptional performance on computer vision benchmarks like nuScenes. ...
Due to calibration errors, misalignment, or inconsistent sampling frequencies among sensors, the data inputs are frequently subject to various degrees of bias and inaccuracies. ...
arXiv:2402.11677v3
fatcat:asireuqi6zgjxmqkgunzfmfkwe
Robust digital watermarking in videos based on geometric transformations
2010
Proceedings of the international conference on Multimedia - MM '10
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In this paper, we present a novel watermarking scheme for videos based on affine geometric transformations. ...
To evaluate our approach, we compare it with several other schemes regarding the robustness against common attacks, including camcorder capture. ...
Also, the geometric misalignment resulting from distortions has to be compensated (spatial synchronization), in order to be able to detect the transformations used for encoding data. ...
doi:10.1145/1873951.1874191
dblp:conf/mm/SchaberKBE10
fatcat:dyrpnvwbjbgxnbthj4fh3tr42u
fRegGAN with K-space Loss Regularization for Medical Image Translation
[article]
2023
arXiv
pre-print
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2023 pre-print arXiv:2303.15938v1 fatcat:rq5z5atmyrfd3l23kh7tnqsxoq
The framework employs a K-space loss to regularize the frequency content of the generated images and incorporates well-known properties of MRI K-space geometry to guide the network training process. ...
By combine our method with the RegGAN approach, we can mitigate the effect of training with misaligned data and frequency bias at the same time. ...
fit the misaligned noise distribution. ...
arXiv:2303.15938v2
fatcat:s4xxzcf3gbapdm6wrdaez7op34
Petascale pipeline for precise alignment of images from serial section electron microscopy
[article]
2022
bioRxiv
pre-print
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For speedup the series is divided into blocks that are distributed to computational workers for alignment. ...
A procedure called vector voting increases robustness to image artifacts or missing image data. ...
Misalignments can be the dominant cause of errors in the automated reconstructions, so it is important for the alignment to be precise and robust to image artifacts. ...
doi:10.1101/2022.03.25.485816
fatcat:2urpoyr2knfofh4lmd5f7pbwwa
Petascale neural circuit reconstruction: automated methods
[article]
2021
bioRxiv
pre-print
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To scale up to larger volumes, we have built a computational pipeline for processing petascale image datasets acquired by serial section EM, a popular form of 3D EM. ...
The pipeline employs convolutional nets to compute the nonsmooth transformations required to align images of serial sections containing numerous cracks and folds, detect neuronal boundaries, label voxels ...
We thank the Manufacturing and Processing Engineering team at the AIBS for their help in implementing the EM imaging and sectioning pipeline. ...
doi:10.1101/2021.08.04.455162
fatcat:puodw2q345eatmvqs4p6rnldym
A Novel Fault Diagnosis Method for Rotating Machinery Based on a Convolutional Neural Network
2018
Sensors
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Thus, a novel diagnosis method is proposed involving the use of a convolutional neural network (CNN) to directly classify the continuous wavelet transform scalogram (CWTS), which is a time-frequency domain ...
transform of the original signal and can contain most of the information of the vibration signals. ...
The continuous wavelet transform is an ideal tool for signal time-frequency analysis and processing. ...
doi:10.3390/s18051429
pmid:29734704
pmcid:PMC5982639
fatcat:jlwosist35btlivr4qd2a22guu
A Motion Correction Strategy for Multi-Contrast based 3D parametric imaging: Application to Inhomogeneous Magnetization Transfer (ihMT)
[article]
2020
bioRxiv
pre-print
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Results Both motion correction strategies significantly reduced inter-image misalignment, and the MC-MoCo method yielded significantly better results than MCFLIRT. ...
Methods A framework for motion correction, including image pre-processing enhancement and rigid registration to an iteratively improved target image, was developed. ...
Compensation schemes to account for images misalignment must thus be considered. ...
doi:10.1101/2020.09.11.292649
fatcat:shooargvv5acfiuqn3csa4nhby
Unsupervised-learning-based method for chest MRI-CT transformation using structure constrained unsupervised generative attention networks
[article]
2021
arXiv
pre-print
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Although PET/MRI facilitates the capture of high-accuracy fusion images, its major drawback can be attributed to the difficulty encountered when performing attenuation correction, which is necessary for ...
unpaired images. ...
Taking the transformation between MRI and CT images as an example, there is a loss (G loss) to make the synthesised CT image closer to the real CT image for the generator, and a loss (D loss) to distinguish ...
arXiv:2106.08557v1
fatcat:fhtqpo7merdnncorn24th5d3ne
Misaligned RGB-Infrared Object Detection via Adaptive Dual-Discrepancy Calibration
2023
Remote Sensing
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Object detection based on RGB and infrared images has emerged as a crucial research area in computer vision, and the synergy of RGB-Infrared ensures the robustness of object-detection algorithms under ...
However, the RGB-IR image pairs captured typically exhibit spatial misalignment due to sensor discrepancies, leading to compromised localization performance. ...
Spatial misalignment: Since RGB and infrared sensors have different coordinate systems, fields of view, and sampling frequencies, pairs of RGB and infrared images usually are spatial misaligned [21] , ...
doi:10.3390/rs15194887
fatcat:mbr52vsedjgipodeg44a4gfjkq
A Study on Deep Learning Application of Vibration Data and Visualization of Defects for Predictive Maintenance of Gravity Acceleration Equipment
2021
Applied Sciences
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(STFT) or Mel-Frequency Cepstral Coefficients (MFCC) spectrogram and converting the input into a 2D image. ...
Hypergravity accelerators are a type of large machinery used for gravity training or medical research. A failure of such large equipment can be a serious problem in terms of safety or costs. ...
The first 200 epochs were used for a more robust model. ...
doi:10.3390/app11041564
fatcat:sullb6xhw5hirkaf6pietn2afi
EleGANt: Exquisite and Locally Editable GAN for Makeup Transfer
[article]
2022
arXiv
pre-print
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To this end, we propose Exquisite and locally editable GAN for makeup transfer (EleGANt). It encodes facial attributes into pyramidal feature maps to preserves high-frequency information. ...
Most existing methods view makeup transfer as transferring color distributions of different facial regions and ignore details such as eye shadows and blushes. ...
Thanks to Steve Lin for his pre-reading and constructive suggestions. ...
arXiv:2207.09840v1
fatcat:ptxo4websvh6hflencycesxhle
Enhancing Low-Light Images in Real World via Cross-Image Disentanglement
[article]
2022
arXiv
pre-print
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In this paper, instead of using perfectly aligned images for training, we creatively employ the misaligned real-world images as the guidance, which are considerably easier to collect. ...
Furthermore, we collect a new low-light image enhancement dataset consisting of misaligned training images with real-world corruptions. ...
Losses for Training Content consistency loss. ...
arXiv:2201.03145v2
fatcat:rftcpihqovetrnvcrvoxehj5y4
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