F2Net: Learning to Focus on the Foreground for Unsupervised Video Object Segmentation

Authors

  • Daizong Liu Huazhong University of Science and Technology, China
  • Dongdong Yu ByteDance AI Lab, China
  • Changhu Wang ByteDance AI Lab, China
  • Pan Zhou Huazhong University of Science and Technology, China

Keywords:

Segmentation

Abstract

Although deep learning based methods have achieved great progress in unsupervised video object segmentation, difficult scenarios (e.g., visual similarity, occlusions, and appearance changing) are still no well-handled. To alleviate these issues, we propose a novel Focus on Foreground Network (F2Net), which delves into the intra-inter frame details for the foreground objects and thus effectively improve the segmentation performance. Specifically, our proposed network consists of three main parts: Siamese Encoder Module, Center Guiding Appearance Diffusion Module, and Dynamic Information Fusion Module. Firstly, we take a siamese encoder to extract the feature representations of paired frames (reference frame and current frame). Then, a Center Guiding Appearance Diffusion Module is designed to capture the inter-frame feature (dense correspondences between reference frame and current frame), intra-frame feature (dense correspondences in current frame), and original semantic feature of current frame. Different from the Anchor Diffusion Network, we establish a Center Prediction Branch to predict the center location of the foreground object in current frame and leverage the center point information as spatial guidance prior to enhance the inter-frame and intra-frame feature extraction, and thus the feature representation considerably focus on the foreground objects. Finally, we propose a Dynamic Information Fusion Module to automatically select relatively important features through three aforementioned different level features. Extensive experiments on DAVIS, Youtube-object, and FBMS datasets show that our proposed F2Net achieves the state-of-the-art performance with significant improvement.

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Published

2021-05-18

How to Cite

Liu, D., Yu, D., Wang, C., & Zhou, P. (2021). F2Net: Learning to Focus on the Foreground for Unsupervised Video Object Segmentation. Proceedings of the AAAI Conference on Artificial Intelligence, 35(3), 2109-2117. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/16308

Issue

Section

AAAI Technical Track on Computer Vision II