Search Results for author: Vishwanath A. Sindagi

Found 19 papers, 7 papers with code

Unsupervised Domain Adaptation of Object Detectors: A Survey

no code implementations27 May 2021 Poojan Oza, Vishwanath A. Sindagi, Vibashan VS, Vishal M. Patel

Recent advances in deep learning have led to the development of accurate and efficient models for various computer vision applications such as classification, segmentation, and detection.

Autonomous Navigation Object Classification +3

KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation

1 code implementation4 Oct 2020 Jeya Maria Jose Valanarasu, Vishwanath A. Sindagi, Ilker Hacihaliloglu, Vishal M. Patel

To overcome this issue, we propose using an overcomplete convolutional architecture where we project our input image into a higher dimension such that we constrain the receptive field from increasing in the deep layers of the network.

3D Medical Imaging Segmentation Brain Tumor Segmentation +4

Learning to Count in the Crowd from Limited Labeled Data

no code implementations ECCV 2020 Vishwanath A. Sindagi, Rajeev Yasarla, Deepak Sam Babu, R. Venkatesh Babu, Vishal M. Patel

In this work, we focus on reducing the annotation efforts by learning to count in the crowd from limited number of labeled samples while leveraging a large pool of unlabeled data.

Crowd Counting

JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Method

no code implementations7 Apr 2020 Vishwanath A. Sindagi, Rajeev Yasarla, Vishal M. Patel

The proposed Confidence Guided Deep Residual Counting Network (CG-DRCN) is evaluated on recent complex datasets, and it achieves significant improvements in errors.

Crowd Counting

Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions

no code implementations ECCV 2020 Vishwanath A. Sindagi, Poojan Oza, Rajeev Yasarla, Vishal M. Patel

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.

Object Detection

Pushing the Frontiers of Unconstrained Crowd Counting: New Dataset and Benchmark Method

no code implementations ICCV 2019 Vishwanath A. Sindagi, Rajeev Yasarla, Vishal M. Patel

The proposed Confidence Guided Deep Residual Counting Network (CG-DRCN) is evaluated on recent complex datasets, and it achieves significant improvements in errors.

Crowd Counting

HA-CCN: Hierarchical Attention-based Crowd Counting Network

no code implementations24 Jul 2019 Vishwanath A. Sindagi, Vishal M. Patel

The proposed method, which is based on the VGG16 network, consists of a spatial attention module (SAM) and a set of global attention modules (GAM).

Crowd Counting

Inverse Attention Guided Deep Crowd Counting Network

no code implementations2 Jul 2019 Vishwanath A. Sindagi, Vishal M. Patel

In this paper, we address the challenging problem of crowd counting in congested scenes.

Crowd Counting

MVX-Net: Multimodal VoxelNet for 3D Object Detection

1 code implementation2 Apr 2019 Vishwanath A. Sindagi, Yin Zhou, Oncel Tuzel

Many recent works on 3D object detection have focused on designing neural network architectures that can consume point cloud data.

3D Object Detection

DAFE-FD: Density Aware Feature Enrichment for Face Detection

no code implementations16 Jan 2019 Vishwanath A. Sindagi, Vishal M. Patel

In this work, we approach the problem of small face detection with the motivation of enriching the feature maps using a density map estimation module.

Crowd Counting Density Estimation +1

Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results

no code implementations26 Apr 2018 Hajime Nada, Vishwanath A. Sindagi, He Zhang, Vishal M. Patel

In this work, we identify the next set of challenges that requires attention from the research community and collect a new dataset of face images that involve these issues such as weather-based degradations, motion blur, focus blur and several others.

Face Detection Robust Face Recognition

High-Quality Facial Photo-Sketch Synthesis Using Multi-Adversarial Networks

1 code implementation27 Oct 2017 Lidan Wang, Vishwanath A. Sindagi, Vishal M. Patel

To this end, we propose a novel synthesis framework called Photo-Sketch Synthesis using Multi-Adversarial Networks, (PS2-MAN) that iteratively generates low resolution to high resolution images in an adversarial way.

Face Sketch Synthesis Image Quality Assessment +2

GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks

2 code implementations3 Oct 2017 Xing Di, Vishwanath A. Sindagi, Vishal M. Patel

The primary aim of this work is to demonstrate that information preserved by landmarks (gender in particular) can be further accentuated by leveraging generative models to synthesize corresponding faces.

Face Generation

Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs

no code implementations ICCV 2017 Vishwanath A. Sindagi, Vishal M. Patel

DME is a multi-column architecture-based CNN that aims to generate high-dimensional feature maps from the input image which are fused with the contextual information estimated by GCE and LCE using F-CNN.

Crowd Counting

A Survey of Recent Advances in CNN-based Single Image Crowd Counting and Density Estimation

1 code implementation5 Jul 2017 Vishwanath A. Sindagi, Vishal M. Patel

Nevertheless, over the last few years, crowd count analysis has evolved from earlier methods that are often limited to small variations in crowd density and scales to the current state-of-the-art methods that have developed the ability to perform successfully on a wide range of scenarios.

Crowd Counting Density Estimation

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