Hierarchical Paired Channel Fusion Network for Street Scene Change Detection

You are here

Top Reasons to Join SPS Today!

1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.

Hierarchical Paired Channel Fusion Network for Street Scene Change Detection

Yinjie Lei, Duo Peng, Pingping Zhang, Qiuhong Ke, Haifeng Li

Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging task in the computer vision community. The intuitive way to solve the SSCD task is to fuse the extracted image feature pairs, and then directly measure the dissimilarity parts for producing a change map. Therefore, the key for the SSCD task is to design an effective feature fusion method that can improve the accuracy of the corresponding change maps. To this end, we present a novel Hierarchical Paired Channel Fusion Network (HPCFNet), which utilizes the adaptive fusion of paired feature channels. Specifically, the features of a given image pair are jointly extracted by a Siamese Convolutional Neural Network (SCNN) and hierarchically combined by exploring the fusion of channel pairs at multiple feature levels. In addition, based on the observation that the distribution of scene changes is diverse, we further propose a Multi-Part Feature Learning (MPFL) strategy to detect diverse changes. Based on the MPFL strategy, our framework achieves a novel approach to adapt to the scale and location diversities of the scene change regions. Extensive experiments on three public datasets (i.e., PCD, VL-CMU-CD and CDnet2014) demonstrate that the proposed framework achieves superior performance which outperforms other state-of-the-art methods with a considerable margin.

SPS on Twitter

  • The Brain Space Initiative Talk Series continues this Friday, 24 September at 11:00 AM EDT when Dr. Jessica Damoise… https://t.co/DHFOzEXvMJ
  • The 2022 membership year has begun! Join our community of more than 17,000 signal processing and data science profe… https://t.co/arfJKa0oaW
  • Join us this Tuesday, 21 September for the Women in Signal Processing event at ICIP 2021! Registration available on… https://t.co/hXXZ61zLBe
  • The SPACE Webinar Series continues this Tuesday, 21 September when Dr. Bin Dong presents "Data- and Task-Driven CT… https://t.co/dkwz0lb2Jk
  • Join SPS President Ahmed Tewfik on Wednesday, 22 September for the IEEE Signal Processing Society Town Hall in conj… https://t.co/31AOCWXvam

SPS Videos

Signal Processing in Home Assistants


Multimedia Forensics

Careers in Signal Processing             


Under the Radar