640 citations · 3.8k across the 145 of their papers we have counts for
23 papers · 1 filter
Overcomplete Representations Against Adversarial Videos
Shao-Yuan Lo, Jeya Maria Jose Valanarasu, Vishal M. Patel
Adversarial robustness of deep neural networks is an extensively studied problem in the literature and various methods have been proposed to defend against adversarial images. Howe…
Overcomplete Deep Subspace Clustering Networks
Jeya Maria Jose Valanarasu, Vishal M. Patel
Deep Subspace Clustering Networks (DSC) provide an efficient solution to the problem of unsupervised subspace clustering by using an undercomplete deep auto-encoder with a fully-co…
Deep Image Compositing
He Zhang, Jianming Zhang, Federico Perazzi +2
Image compositing is a task of combining regions from different images to compose a new image. A common use case is background replacement of portrait images. To obtain high qualit…
CR-Fill: Generative Image Inpainting with Auxiliary Contexutal Reconstruction
Yu Zeng, Zhe Lin, Huchuan Lu +1
Recent deep generative inpainting methods use attention layers to allow the generator to explicitly borrow feature patches from the known region to complete a missing region. Due t…
Exploring Overcomplete Representations for Single Image Deraining using CNNs
Rajeev Yasarla, Jeya Maria Jose Valanarasu, Vishal M. Patel
Removal of rain streaks from a single image is an extremely challenging problem since the rainy images often contain rain streaks of different size, shape, direction and density. M…
KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation
Jeya Maria Jose Valanarasu, Vishwanath A. Sindagi, Ilker Hacihaliloglu +1
Most methods for medical image segmentation use U-Net or its variants as they have been successful in most of the applications. After a detailed analysis of these "traditional" enc…
Semi-Supervised Image Deraining using Gaussian Processes
Rajeev Yasarla, V. A. Sindagi, V. M. Patel
Recent CNN-based methods for image deraining have achieved excellent performance in terms of reconstruction error as well as visual quality. However, these methods are limited in t…
Completely Self-Supervised Crowd Counting via Distribution Matching
Deepak Babu Sam, Abhinav Agarwalla, Jimmy Joseph +3
Dense crowd counting is a challenging task that demands millions of head annotations for training models. Though existing self-supervised approaches could learn good representation…
Open-set Adversarial Defense
Rui Shao, Pramuditha Perera, Pong C. Yuen +1
Open-set recognition and adversarial defense study two key aspects of deep learning that are vital for real-world deployment. The objective of open-set recognition is to identify s…
MultAV: Multiplicative Adversarial Videos
Shao-Yuan Lo, Vishal M. Patel
The majority of adversarial machine learning research focuses on additive attacks, which add adversarial perturbation to input data. On the other hand, unlike image recognition pro…
Defending Against Multiple and Unforeseen Adversarial Videos
Shao-Yuan Lo, Vishal M. Patel
Adversarial robustness of deep neural networks has been actively investigated. However, most existing defense approaches are limited to a specific type of adversarial perturbations…
Confidence-guided Lesion Mask-based Simultaneous Synthesis of Anatomic and Molecular MR Images in Patients with Post-treatment Malignant Gliomas
Pengfei Guo, Puyang Wang, Rajeev Yasarla +3
Data-driven automatic approaches have demonstrated their great potential in resolving various clinical diagnostic dilemmas in neuro-oncology, especially with the help of standard a…
Learning to Restore a Single Face Image Degraded by Atmospheric Turbulence using CNNs
Rajeev Yasarla, Vishal M Patel
Atmospheric turbulence significantly affects imaging systems which use light that has propagated through long atmospheric paths. Images captured under such condition suffer from a…
Anomaly Detection-Based Unknown Face Presentation Attack Detection
Yashasvi Baweja, Poojan Oza, Pramuditha Perera +1
Anomaly detection-based spoof attack detection is a recent development in face Presentation Attack Detection (fPAD), where a spoof detector is learned using only non-attacked image…
Few Is Enough: Task-Augmented Active Meta-Learning for Brain Cell Classification
Pengyu Yuan, Aryan Mobiny, Jahandar Jahanipour +6
Deep Neural Networks (or DNNs) must constantly cope with distribution changes in the input data when the task of interest or the data collection protocol changes. Retraining a netw…
Learning to Count in the Crowd from Limited Labeled Data
Vishwanath A. Sindagi, Rajeev Yasarla, Deepak Sam Babu +2
Recent crowd counting approaches have achieved excellent performance. However, they are essentially based on fully supervised paradigm and require large number of annotated samples…
KiU-Net: Towards Accurate Segmentation of Biomedical Images using Over-complete Representations
Jeya Maria Jose, Vishwanath Sindagi, Ilker Hacihaliloglu +1
Due to its excellent performance, U-Net is the most widely used backbone architecture for biomedical image segmentation in the recent years. However, in our studies, we observe tha…
Quickest Intruder Detection for Multiple User Active Authentication
Pramuditha Perera, Julian Fierrez, Vishal M. Patel
In this paper, we investigate how to detect intruders with low latency for Active Authentication (AA) systems with multiple-users. We extend the Quickest Change Detection (QCD) fra…
Syn2Real Transfer Learning for Image Deraining using Gaussian Processes
Rajeev Yasarla, Vishwanath A. Sindagi, Vishal M. Patel
Recent CNN-based methods for image deraining have achieved excellent performance in terms of reconstruction error as well as visual quality. However, these methods are limited in t…
Lesion Mask-based Simultaneous Synthesis of Anatomic and MolecularMR Images using a GAN
Pengfei Guo, Puyang Wang, Jinyuan Zhou +2
Data-driven automatic approaches have demonstrated their great potential in resolving various clinical diagnostic dilemmas for patients with malignant gliomas in neuro-oncology wit…
Federated Face Presentation Attack Detection
Rui Shao, Pramuditha Perera, Pong C. Yuen +1
Face presentation attack detection (fPAD) plays a critical role in the modern face recognition pipeline. A face presentation attack detection model with good generalization can be…
Multi-Scale Thermal to Visible Face Verification via Attribute Guided Synthesis
Xing Di, Benjamin S. Riggan, Shuowen Hu +2
Thermal-to-visible face verification is a challenging problem due to the large domain discrepancy between the modalities. Existing approaches either attempt to synthesize visible f…
JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Method
Vishwanath A. Sindagi, Rajeev Yasarla, Vishal M. Patel
Due to its variety of applications in the real-world, the task of single image-based crowd counting has received a lot of interest in the recent years. Recently, several approaches…