Browsing by Advisor "Venkatesh Babu, R"
Now showing items 1-10 of 10
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Advances in High Dynamic Range Imaging Using Deep Learning
Natural scenes have a wide range of brightness, from dark starry nights to bright sunlit beaches. Our human eyes can perceive such a vast range of illumination through various adaptation techniques, thus allowing us to ... -
Approximate Nearest Neighbour Field Computation and Applications
(2018-05-09)Approximate Nearest-Neighbour Field (ANNF\ maps between two related images are commonly used by computer vision and graphics community for image editing, completion, retargetting and denoising. In this work we generalize ... -
Deep Learning for Hand-drawn Sketches: Analysis, Synthesis and Cognitive Process Models
Deep Learning-based object category understanding is an important and active area of research in Computer Vision. Most work in this area has predominantly focused on the portion of depiction spectrum consisting of ... -
Deep Visual Representations: A study on Augmentation, Visualization, and Robustness
Deep neural networks have resulted in unprecedented performances for various learning tasks. Particularly, Convolutional Neural Networks (CNNs) are shown to learn representations that can efficiently discriminate hundreds ... -
Exploring the Inherent Saliency in Visual Data through Convolutional Neural Networks
Saliency plays a key role in various computer vision tasks. Extracting salient regions from images and videos has been a well-established problem in computer vision. Determining salient regions in an image or video has ... -
Learning Compact Architectures for Deep Neural Networks
(2018-05-22)Deep neural networks with millions of parameters are at the heart of many state of the art computer vision models. However, recent works have shown that models with much smaller number of parameters can often perform just ... -
Motion Based Event Analysis
(2018-05-09)Motion is an important cue in videos that captures the dynamics of moving objects. It helps in effective analysis of various event related tasks such as human action recognition, anomaly detection, tracking, crowd behavior ... -
Self-Supervised Domain Adaptation Frameworks for Computer Vision Tasks
There is a strong incentive to build intelligent machines that can understand and adapt to changes in the visual world without human supervision. While humans and animals learn to perceive the world on their own, almost ... -
A study on Deep Learning Approaches, Architectures and Training Methods for Crowd Analysis
Analyzing large crowds quickly is one of the highly sought-after capabilities nowadays. Especially in terms of public security and planning, this assumes prime importance. But automated reasoning of crowd images or videos ... -
Towards Learning Adversarially Robust Deep Learning Models
Deep learning models have shown impressive performance across a wide spectrum of computer vision applications, including medical diagnosis and autonomous driving. One of the major concerns that these models face is their ...