Multispectral pedestrian detection has received great attention in recent years as
multispectral modalities (ie color and thermal) can provide complementary visual …

Drone-view Object Detection (DOD) is a meaningful but challenging task. It hits a bottleneck
due to two main reasons:(1) The high proportion of difficult objects (eg, small objects …

Object detection became one of the major fields in computer vision. In object detection,
object classification and object localization tasks are conducted. Previous deep learning …

Single-stage detectors have gained great attention due to their high detection accuracy and
real-time speed. To detect multi-scale objects, single-stage detectors make scale-aware …

Person search aims to localize and identify specific pedestrians from numerous surveillance
scene images. In this work, we focus on the noise in person search. We categorize the noise …

Target detection in high-contrast, multi-object images and movies is challenging. This
difficulty results from different areas and objects/people having varying pixel distributions …

In this paper, we present a dense hybrid proposal modulation (DHPM) method for lane
detection. Most existing methods perform sparse supervision on a subset of high-scoring …

A DCNN-LSTM (Deep Convolutional Neural Network-Long Short Term Memory) model is
proposed to recognize and track table tennis's real-time trajectory in complex environments …

Multispectral object detection (MOD), which incorporates additional information from thermal
images into object detection (OD) to robustly cope with complex illumination conditions, has …

Most recent object detection methods have achieved growing performance on public
datasets. However, enormous efforts are needed for these methods due to the extensive …