Call for papers of a special issue on Deep Video Analysis: Models, Algorithms and Applications

  in Special Issue   Posted on June 12, 2019

Information for the Special Issue

Submission Deadline: Mon 30 Sep 2019
Journal Impact Factor : 4.582
Journal Name : Pattern Recognition
Journal Publisher:
Website for the Special Issue:
Journal & Submission Website:

Special Issue Call for Papers:

Aim and Scope

Video analysis is an important research area in pattern recognition and computer vision. The past decades have witnessed the rapid expansion of the video data generated every day including video surveillance, personal mobile device capture, and webs upload. It is quite needed for understanding such a large amount of video data. Meanwhile, deep learning, as a fast-growing research field, showed a vast success over a wide of research areas. The combination of the big visual data and the deep learning paradigm would bring a significant progress in both video analysis and life-related applications. However, the current capability gap of deep learning to handle video analysis is still huge. This mainly because video data conveys rich spatial and temporal information. In addition, the annotation of video labels especially pixel-level labels is expensively-acquired, which limits the further learning of deep neural networks. Thus, there is a pressing demand for novel deep learning based video analysis approaches that can cope with video analysis task with better accuracy and efficiency. In this special issue, we attempt to assemble recent advances in the deep learning based video analysis and related extended applications.

This special issue will feature original research papers related to the models and algorithm for various video analysis tasks from the low-level (e.g., video processing) to high-level (e.g., spatiotemporal reasoning), together with widespread applications to real-world issues. The main topics of interest (but are not limited to):

— Learning data representation from video based on supervised/unsupervised/semi-supervised learning.

—Video object tracking and segmentation: 1) Single object/multiple objects tracking; 2) Video segmentation; 3) Object saliency prediction.

—Optical flow estimation and visual SLAM.

—Person re-identification, multiple-camera tracking and vehicle re-identification, and human pose estimation/tracking.

—Dynamic scene parsing and semantic video segmentation.

—Video understanding: 1) Video classification and spatiotemporal reasoning; 2) Video action recognition; 3) Video summarization/video captioning; 4) Video generation; 5) Video anomaly detection.

—Applications: Applications of the corresponding methods to solve real-world video analysis issues including robot visions, machine visions, video object detection etc.

—New benchmark datasets related to the aforementioned topics.

Important dates:

Submission deadline: April 15-May 31, 2019

First review notification: July 30, 2019

Revised submission due: September 30, 2019

Final acceptance: November 30, 2019


Wenguan Wang

Research Scientist

Inception Institute of Artificial Intelligence, UAE


Haibin Ling

Associate Professor

Temple University, USA


Chao Ma

Senior Research Associate

The University of Adelaide, Australia


Xiankai Lu

Research Scientist

Inception Institute of Artificial Intelligence, UAE


Fatih Porikli


Australian National University, Australia


Submission Guidelines:

Manuscript must be within the scope of Pattern Recognition journal. Manuscript preparation guidelines are available at All papers will be handled via Elsevier Editorial System: Please select \”SI: DVA\” when selecting article type name during the submission process.

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