5 accepted papers
Driving requires reacting to a wide variety of complex environment conditions and agent behaviors. Explicitly modeling each possible scenario is unrealistic. In contrast, imitation learning can, in theory, leverage data from large fleets of human-driven cars. Behavior cloning in particular has been…
It is almost seventy years after the publication of Claude Shannon's “A Mathematical Theory of Communication” [1] and Norbert Wiener's “Extrapolation, Interpolation and Smoothing of Stationary Time Series” [2]. The pioneering works of Shannon and Wiener lay the foundation of communication, data stor…
We investigate a neural network architecture and statistical framework that models frames in videos using principles inspired by computer graphics pipelines. The proposed model explicitly represents "sprites" or its percepts inferred from maximum likelihood of the scene and infers its movement indep…
Saliency measures are a popular way to predict visual attention. However, saliency is normally tested on sets of single resolution images that are unlike what the human vision system sees. We propose a new saliency measure based on convolving images with 2D gamma kernels which function as a comparis…
In this paper we investigate the advantages of learning representations of color plus depth images (Red-Blue-Green-Depth, RGB-D) over color only images (RGB) for computer vision. Specifically, we investigate the advantages on the task of object recognition. For this purpose, we applied the state-of-…