Pedestrian detection relying on deep convolution neural networks has made significant
progress. Though promising results have been achieved on standard pedestrians, the …

Occlusions present a great challenge for pedestrian detection in practical applications. In
this paper, we propose a novel approach to simultaneous pedestrian detection and …

Recent pedestrian detection methods generally rely on additional supervision, such as
visible bounding-box annotations, to handle heavy occlusions. We propose an approach …

Despite recent progress of pedestrian detection, it remains a challenging problem to detect
pedestrians that are partially occluded due to the uncertainty and diversity of partial …

Detecting pedestrians and their associated faces jointly is a challenging task. On one hand,
body or face could be absent because of occlusion or non-frontal human pose. On the other …

State-of-the-art pedestrian detectors have achieved significant progress on non-occluded
pedestrians, yet they are still struggling under heavy occlusions. The recent occlusion …

Object detection using shape is interesting since it is well known that humans can recognize
an object simply from its shape. Thus, shape-based methods have great promise to handle a …

Detecting partially occluded objects is difficult due to the appearances and shapes of
occluders are highly variable. These variabilities lead to challenges of localizing accurate …

Object Detection using shape is interesting since it is well known that humans can recognise
an object simply from its shape. Thus, shape-based methods have great promise to handle a …

Middle-level parts have attracted great attention in the computer vision community, acting as
discriminative elements for objects. In this paper we propose an unsupervised approach to …