Methods › Computer Vision › Semantic Segmentation Models › BASNet

Boundary-Aware Segmentation Network

BASNet

4 papers tagged archive 2025-07-28

Introduced by Xuebin Qin et al. in Boundary-Aware Segmentation Network for Mobile and Web Applications

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

BASNet, or Boundary-Aware Segmentation Network, is an image segmentation architecture that consists of a predict-refine architecture and a hybrid loss. The proposed BASNet comprises a predict-refine architecture and a hybrid loss, for highly accurate image segmentation. The predict-refine architecture consists of a densely supervised encoder-decoder network and a residual refinement module, which are respectively used to predict and refine a segmentation probability map. The hybrid loss is a combination of the binary cross entropy, structural similarity and intersection-over-union losses, which guide the network to learn three-level (i.e., pixel-, patch- and map- level) hierarchy representations.

Paper Source

Papers archive 2025-07-28

4 shown of 4, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

UDBRNet: A novel uncertainty driven boundary refined network for organ at risk segmentation
17 Jun 2024 · 1 repository
To be Critical: Self-Calibrated Weakly Supervised Learning for Salient Object Detection
4 Sep 2021 · 0 repositories · arXiv:2109.01770
Weakly-Supervised Temporal Action Localization Through Local-Global Background Modeling
20 Jun 2021 · 0 repositories · arXiv:2106.11811
Boundary-Aware Segmentation Network for Mobile and Web Applications
12 Jan 2021 · 5 repositories · arXiv:2101.04704

Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)

Tasks archive 2025-07-28

15 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

Task	Papers
Segmentation	2
Weakly-supervised Learning	2
Action Localization	1
Camouflaged Object Segmentation	1
Decoder	1
GPU	1
Image Segmentation	1
Object	1
Object Detection	1
Organ Segmentation	1
Salient Object Detection	1
Semantic Segmentation	1
Temporal Action Localization	1
Weakly-supervised Temporal Action Localization	1
object-detection	1

Usage over time archive 2025-07-28

Papers per year the archive tags with this method, by the paper's archive date (4 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Semantic Segmentation Models

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