One of the core problems of modern statistics is to approximate difficult-to-compute
probability densities. This problem is especially important in Bayesian statistics, which …

Animals have evolved highly functional visual systems to understand motion, assisting
perception even under complex environments. In this paper, we work towards developing a …

Video object segmentation is challenging due to fast moving objects, deforming shapes, and
cluttered backgrounds. Optical flow can be used to propagate an object segmentation over …

We describe a latent approach that learns to detect actions in long sequences given training
videos with only whole-video class labels. Our approach makes use of two innovations to …

We propose a strong baseline model for unsupervised feature learning using video data. By
learning to predict missing frames or extrapolate future frames from an input video …

Many real world tasks such as reasoning and physical interaction require identification and
manipulation of conceptual entities. A first step towards solving these tasks is the automated …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …

We describe a method to extract persistent elements of a dynamic scene from an input
video. We represent each scene element as a Deformable Sprite consisting of three …

The focus of motion analysis has been on estimating a flow vector for every pixel by
matching intensities. In my thesis, I will explore motion representations beyond the pixel …

We present a unified computational approach for taking photos through reflecting or
occluding elements such as windows and fences. Rather than capturing a single image, we …