My research interests are broadly in the areas of image and video processing, computer vision and using machine learning tools for the same. Specific interests are outlined below:
- Video Quality Assessment (VQA): For various applications, it is desirable to assess the quality of videos. For those where humans would be the end users, the best and accurate method to evaluate the quality of the videos would be through a subjective study. Since subjective studies are cumbersome and difficult to scale, it is desirable to have an objective measure of quality, that correlates well with human judgement. VQA deals with designing objective measures to predict the quality of a given video. I'm interested in both statistical methods of evaluation as well as using deep neural networks.
- Video Prediction: Video Prediction refers to the problem to predicting future frames given a few past frames. This problem has gained traction with the recent success of deep learning and generative models. This problem has applications in video representation learning, anomaly detection, video compression, self driving cars and robotic path planning.