Vessel Detection

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

10 shown of 10 papers with code (29 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
  4 Jun 2015 196 repositories listed Syntology ran 59 of 124 samples · 65 unverified · 42 pointer-only (licence)
  In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals.
• Deformable Convolutional Networks
  17 Mar 2017 38 repositories listed Syntology ran 3 of 9 samples · 6 unverified · 3 pointer-only (licence)
  Convolutional neural networks (CNNs) are inherently limited to model geometric transformations due to the fixed geometric structures in its building modules.
• CE-Net: Context Encoder Network for 2D Medical Image Segmentation
  7 Mar 2019 3 repositories listed
  In this paper, we propose a context encoder network (referred to as CE-Net) to capture more high-level information and preserve spatial information for 2D medical image segmentation.
• Asynchronous Trajectory Matching-Based Multimodal Maritime Data Fusion for Vessel Traffic Surveillance in Inland Waterways
  22 Feb 2023 2 repositories listed
  To further improve vessel traffic surveillance, it becomes necessary to fuse the AIS and video data to simultaneously capture the visual features, identity and dynamic information for the vessels of interest.
• Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation
  18 Jan 2025 1 repository listed
  Accurate segmentation of the aorta and its associated arch branches is crucial for diagnosing aortic diseases.
• Image and AIS Data Fusion Technique for Maritime Computer Vision Applications
  7 Dec 2023 1 repository listed
  This demonstrates the potential of our approach in creating datasets for vessel detection, pose estimation and auto-labelling pipelines.
• A Sequence Agnostic Multimodal Preprocessing for Clogged Blood Vessel Detection in Alzheimer's Diagnosis
  6 Nov 2022 1 repository listed
  Successful identification of blood vessel blockage is a crucial step for Alzheimer's disease diagnosis.
• Real-Time Event-Based Tracking and Detection for Maritime Environments
  9 Feb 2022 1 repository listed
  Event cameras are ideal for object tracking applications due to their ability to capture fast-moving objects while mitigating latency and data redundancy.
• An Active Contour Model Using Matched Filter and Hessian Matrix for Retinal Vessels Segmentation
  27 Jan 2022 1 repository listed
  To prevent the destruction of the stability of evolution, we used an optimization process formula whose task is to keep contour on the edges of the image.
• Ensemble of Deep Convolutional Neural Networks for Learning to Detect Retinal Vessels in Fundus Images
  15 Mar 2016 1 repository listed
  In this work we present a computational imaging framework using deep and ensemble learning for reliable detection of blood vessels in fundus color images.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.