Search Results for author:
Found 7 papers, 2 papers with code
Movie Recommendation System using Sentiment Analysis from Microblogging Data
Traditional approaches in recommendation systems include collaborative filtering and content-based filtering.
Reconstruction Loss Minimized FCN for Single Image Dehazing
In this paper, we propose a Fully Convolutional Neural Network based model to recover the clear scene radiance by estimating the environmental illumination and the scene transmittance jointly from a hazy image.
Perceptual Conditional Generative Adversarial Networks for End-to-End Image Colourization
Colours are everywhere.
Physics-Based Rendering for Improving Robustness to Rain
Our rendering relies on a physical particle simulator, an estimation of the scene lighting and an accurate rain photometric modeling to augment images with arbitrary amount of realistic rain or fog.
MA 3 : Model Agnostic Adversarial Augmentation for Few Shot learning
Despite the recent developments in vision-related problems using deep neural networks, there still remains a wide scope in the improvement of generalizing these models to unseen examples.
Enhancing Perceptual Loss with Adversarial Feature Matching for Super-Resolution
In this paper, we show that the root cause of these pattern artifacts can be traced back to a mismatch between the pre-training objective of perceptual loss and the super-resolution objective.
Rain rendering for evaluating and improving robustness to bad weather
In this context, we present a rain rendering pipeline that enables the systematic evaluation of common computer vision algorithms to controlled amounts of rain.
