A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Predicting trajectories of multiple agents in interactive driving scenarios such as
intersections, and roundabouts are challenging due to the high density of agents, varying …

Marine ecosystems and their fish habitats are becoming increasingly important due to their
integral role in providing a valuable food source and conservation outcomes. Due to their …

While domain adaptation has been actively researched, most algorithms focus on the single-
source-single-target adaptation setting. In this paper we propose new generalization bounds …

We present a novel method called Contextual Pyramid CNN (CP-CNN) for generating high-
quality crowd density and count estimation by explicitly incorporating global and local …

Automatic estimation of the number of people in unconstrained crowded scenes is a
challenging task and one major difficulty stems from the huge scale variation of people. In …

Crowd counting or density estimation is a challenging task in computer vision due to large
scale variations, perspective distortions and serious occlusions, etc. Existing methods …

Crowd counting is a fundamental yet challenging task, which desires rich information to
generate pixel-wise crowd density maps. However, most previous methods only used the …

Accurately estimating the number of objects in a single image is a challenging yet
meaningful task and has been applied in many applications such as urban planning and …

Crowd counting presents enormous challenges in the form of large variation in scales within
images and across the dataset. These issues are further exacerbated in highly congested …