172 citations · 1.2k across the 80 of their papers we have counts for
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DeepFuse: A Deep Unsupervised Approach for Exposure Fusion with Extreme Exposure Image Pairs
K. Ram Prabhakar, V. Sai Srikar, R. Venkatesh Babu
We present a novel deep learning architecture for fusing static multi-exposure images. Current multi-exposure fusion (MEF) approaches use hand-crafted features to fuse input sequen…
NAG: Network for Adversary Generation
Konda Reddy Mopuri, Utkarsh Ojha, Utsav Garg +1
Adversarial perturbations can pose a serious threat for deploying machine learning systems. Recent works have shown existence of image-agnostic perturbations that can fool classifi…
Switching Convolutional Neural Network for Crowd Counting
Deepak Babu Sam, Shiv Surya, R. Venkatesh Babu
We propose a novel crowd counting model that maps a given crowd scene to its density. Crowd analysis is compounded by myriad of factors like inter-occlusion between people due to e…
Image Denoising via CNNs: An Adversarial Approach
Nithish Divakar, R. Venkatesh Babu
Is it possible to recover an image from its noisy version using convolutional neural networks? This is an interesting problem as convolutional layers are generally used as feature…
Confidence estimation in Deep Neural networks via density modelling
Akshayvarun Subramanya, Suraj Srinivas, R. Venkatesh Babu
State-of-the-art Deep Neural Networks can be easily fooled into providing incorrect high-confidence predictions for images with small amounts of adversarial noise. Does this expose…
Fast Feature Fool: A data independent approach to universal adversarial perturbations
Konda Reddy Mopuri, Utsav Garg, R. Venkatesh Babu
State-of-the-art object recognition Convolutional Neural Networks (CNNs) are shown to be fooled by image agnostic perturbations, called universal adversarial perturbations. It is a…
DeLiGAN : Generative Adversarial Networks for Diverse and Limited Data
Swaminathan Gurumurthy, Ravi Kiran Sarvadevabhatla, Venkatesh Babu Radhakrishnan
A class of recent approaches for generating images, called Generative Adversarial Networks (GAN), have been used to generate impressively realistic images of objects, bedrooms, han…
Deep image representations using caption generators
Konda Reddy Mopuri, Vishal B. Athreya, R. Venkatesh Babu
Deep learning exploits large volumes of labeled data to learn powerful models. When the target dataset is small, it is a common practice to perform transfer learning using pre-trai…