Human-centric perceptions (eg, pose estimation, human parsing, pedestrian detection,
person re-identification, etc.) play a key role in industrial applications of visual models. While …

In this paper, we consider the problem of pedestrian detection in natural scenes. Intuitively,
instances of pedestrians with different spatial scales may exhibit dramatically different …

In this paper, we propose a CNN-based framework for online MOT. This framework utilizes
the merits of single object trackers in adapting appearance models and searching for target …

Motion representation plays a vital role in human action recognition in videos. In this study,
we introduce a novel compact motion representation for video action recognition, named …

Video scene analysis is a recent research topic due to its vital importance in many
applications such as real-time vehicle activity tracking, pedestrian detection, surveillance …

Due to the limited amount of training samples, fine-tuning pre-trained deep models online is
prone to over-fitting. In this paper, we propose a sequential training method for convolutional …

Finetuning from a pretrained deep model is found to yield state-of-the-art performance for
many vision tasks. This paper investigates many factors that influence the performance in …

岩石岩性的识别与分类对于地质分析极为重要, 采用机器学习的方法建立识别模型进行自动分类
是一条新的途径. 基于Inception-v3 深度卷积神经网络模型, 建立了岩石图像集分析的深度学习 …

Feature extraction, deformation handling, occlusion handling, and classification are four
important components in pedestrian detection. Existing methods learn or design these …

Pedestrian Detection is the most critical module of an Autonomous Driving system. Although
a camera is commonly used for this purpose, its quality degrades severely in low-light night …