We investigate conditional adversarial networks as a general-purpose solution to image-to-
image translation problems. These networks not only learn the map** from input image to …

Scene segmentation is a challenging task as it need label every pixel in the image. It is
crucial to exploit discriminative context and aggregate multi-scale features to achieve better …

The traffic state in an urban transportation network is determined via spatio-temporal traffic
propagation. In early traffic forecasting studies, time-series models were adopted to …

We present a novel framework for iterative visual reasoning. Our framework goes beyond
current recognition systems that lack the capability to reason beyond stack of convolutions …

Semantic image segmentation aims to classify every pixel of a scene image to one of many
classes. It implicitly involves object recognition, localization, and boundary delineation. In …

Modeling instance-level context and object-object relationships is extremely challenging. It
requires reasoning about bounding boxes of different locations, scales, aspect ratios etc …

Recently some efforts were made towards capturing the security requirements from digital
signature schemes as an ideal functionality within a composable security framework. This …

Visual semantic information comprises two important parts: the meaning of each visual
semantic unit and the coherent visual semantic relation conveyed by these visual semantic …

In this paper, we address the challenging task of scene segmentation. In order to capture the
rich contextual dependencies over image regions, we propose Directed Acyclic Graph …

A dynamic scene has two types of elements: those that move fluidly and can be predicted
from previous frames, and those which are disoccluded (exposed) and cannot be …