640 citations · 3.8k across the 145 of their papers we have counts for
19 papers · 1 filter
Learning to Segment Brain Anatomy from 2D Ultrasound with Less Data
Jeya Maria Jose V., Rajeev Yasarla, Puyang Wang +2
Automatic segmentation of anatomical landmarks from ultrasound (US) plays an important role in the management of preterm neonates with a very low birth weight due to the increased…
Facial Synthesis from Visual Attributes via Sketch using Multi-Scale Generators
Xing Di, Vishal M. Patel
Automatic synthesis of faces from visual attributes is an important problem in computer vision and has wide applications in law enforcement and entertainment. With the advent of de…
Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions
Vishwanath A. Sindagi, Poojan Oza, Rajeev Yasarla +1
Adverse weather conditions such as haze and rain corrupt the quality of captured images, which cause detection networks trained on clean images to perform poorly on these images. T…
Pushing the Frontiers of Unconstrained Crowd Counting: New Dataset and Benchmark Method
Vishwanath A. Sindagi, Rajeev Yasarla, Vishal M. Patel
In this work, we propose a novel crowd counting network that progressively generates crowd density maps via residual error estimation. The proposed method uses VGG16 as the backbon…
Confidence Measure Guided Single Image De-raining
Rajeev Yasarla, Vishal M. Patel
Single image de-raining is an extremely challenging problem since the rainy images contain rain streaks which often vary in size, direction and density. This varying characteristic…
Multi-Level Bottom-Top and Top-Bottom Feature Fusion for Crowd Counting
Vishwanath A Sindagi, Vishal M. Patel
Crowd counting presents enormous challenges in the form of large variation in scales within images and across the dataset. These issues are further exacerbated in highly congested…
HA-CCN: Hierarchical Attention-based Crowd Counting Network
Vishwanath A. Sindagi, Vishal M. Patel
Single image-based crowd counting has recently witnessed increased focus, but many leading methods are far from optimal, especially in highly congested scenes. In this paper, we pr…
Inverse Attention Guided Deep Crowd Counting Network
Vishwanath A. Sindagi, Vishal M. Patel
In this paper, we address the challenging problem of crowd counting in congested scenes. Specifically, we present Inverse Attention Guided Deep Crowd Counting Network (IA-DCCN) tha…
Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks
Rajeev Yasarla, Federico Perazzi, Vishal M. Patel
We propose a novel multi-stream architecture and training methodology that exploits semantic labels for facial image deblurring. The proposed Uncertainty Guided Multi- Stream Seman…
Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining
Rajeev Yasarla, Vishal M. Patel
Single image de-raining is an extremely challenging problem since the rainy image may contain rain streaks which may vary in size, direction and density. Previous approaches have a…
Deep Sparse Representation-based Classification
Mahdi Abavisani, Vishal M. Patel
We present a transductive deep learning-based formulation for the sparse representation-based classification (SRC) method. The proposed network consists of a convolutional autoenco…
Polarimetric Thermal to Visible Face Verification via Self-Attention Guided Synthesis
Xing Di, Benjamin S. Riggan, Shuowen Hu +2
Polarimetric thermal to visible face verification entails matching two images that contain significant domain differences. Several recent approaches have attempted to synthesize vi…
C2AE: Class Conditioned Auto-Encoder for Open-set Recognition
Poojan Oza, Vishal M Patel
Models trained for classification often assume that all testing classes are known while training. As a result, when presented with an unknown class during testing, such closed-set…
Deep CNN-based Multi-task Learning for Open-Set Recognition
Poojan Oza, Vishal M. Patel
We propose a novel deep convolutional neural network (CNN) based multi-task learning approach for open-set visual recognition. We combine a classifier network and a decoder network…
Deep Transfer Learning for Multiple Class Novelty Detection
Pramuditha Perera, Vishal M. Patel
We propose a transfer learning-based solution for the problem of multiple class novelty detection. In particular, we propose an end-to-end deep-learning based approach in which we…
Active Authentication using an Autoencoder regularized CNN-based One-Class Classifier
Poojan Oza, Vishal M. Patel
Active authentication refers to the process in which users are unobtrusively monitored and authenticated continuously throughout their interactions with mobile devices. Generally,…
One-Class Convolutional Neural Network
Poojan Oza, Vishal M. Patel
We present a novel Convolutional Neural Network (CNN) based approach for one class classification. The idea is to use a zero centered Gaussian noise in the latent space as the pseu…
DAFE-FD: Density Aware Feature Enrichment for Face Detection
Vishwanath A. Sindagi, Vishal M. Patel
Recent research on face detection, which is focused primarily on improving accuracy of detecting smaller faces, attempt to develop new anchor design strategies to facilitate increa…
Polarimetric Thermal to Visible Face Verification via Attribute Preserved Synthesis
Xing Di, He Zhang, Vishal M. Patel
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…