Improving Pixel Embedding Learning Through Intermediate Distance Regression Supervision for Instance Segmentation
Wu Y, Chen L, Merhof D (2020)
Publication Type: Conference contribution
Publication year: 2020
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 12540 LNCS
Pages Range: 213-227
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Glasgow, GBR
ISBN: 9783030654139
DOI: 10.1007/978-3-030-65414-6_16
Abstract
As a proposal-free approach, instance segmentation through pixel embedding learning and clustering is gaining more emphasis. Compared with bounding box refinement approaches, such as Mask R-CNN, it has potential advantages in handling complex shapes and dense objects. In this work, we propose a simple, yet highly effective, architecture for object-aware embedding learning. A distance regression module is incorporated into our architecture to generate seeds for fast clustering. At the same time, we show that the features learned by the distance regression module are able to promote the accuracy of learned object-aware embeddings significantly. By simply concatenating features of the distance regression module to the images as inputs of the embedding module, the mSBD scores on the CVPPP Leaf Segmentation Challenge can be further improved by more than 8% compared to the identical set-up without concatenation, yielding the best overall result amongst the leaderboard at CodaLab.
Involved external institutions
Germany (DE)How to cite
APA:
Wu, Y., Chen, L., & Merhof, D. (2020). Improving Pixel Embedding Learning Through Intermediate Distance Regression Supervision for Instance Segmentation. In Adrien Bartoli, Andrea Fusiello (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 213-227). Glasgow, GBR: Springer Science and Business Media Deutschland GmbH.
MLA:
Wu, Yuli, Long Chen, and Dorit Merhof. "Improving Pixel Embedding Learning Through Intermediate Distance Regression Supervision for Instance Segmentation." Proceedings of the Workshops held at the 16th European Conference on Computer Vision, ECCV 2020, Glasgow, GBR Ed. Adrien Bartoli, Andrea Fusiello, Springer Science and Business Media Deutschland GmbH, 2020. 213-227.
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