Related papers: 4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview

4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview

URL: http://arxiv.org/abs/2604.13244v1
Date: Tue, 14 Apr 2026 19:21:41 GMT
Title: 4th Workshop on Maritime Computer Vision (MaCVi): Challenge Overview
Abstract summary: The 4th Workshop on Maritime Computer Vision (MaCVi) is organized as part of CVPR 2026.<n>This edition features five benchmark challenges with emphasis on both predictive accuracy and embedded real-time feasibility.
Score: 58.58288326268589
License: http://creativecommons.org/licenses/by/4.0/
Abstract: The 4th Workshop on Maritime Computer Vision (MaCVi) is organized as part of CVPR 2026. This edition features five benchmark challenges with emphasis on both predictive accuracy and embedded real-time feasibility. This report summarizes the MaCVi 2026 challenge setup, evaluation protocols, datasets, and benchmark tracks, and presents quantitative results, qualitative comparisons, and cross-challenge analyses of emerging method trends. We also include technical reports from top-performing teams to highlight practical design choices and lessons learned across the benchmark suite. Datasets, leaderboards, and challenge resources are available at https://macvi.org/workshop/cvpr26.

Related papers

Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding [202.7892709083317]
This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge.<n>The 2026 edition features three specialized tracks: the MOSE track for tracking objects within densely cluttered and severely occluded scenarios; the MeViS-Text track for localizing targets via motion-focused linguistic expressions; and the newly inaugurated MeViS-Audio track, which pioneers acoustic-driven object segmentation.
arXiv Detail & Related papers (2026-04-28T18:14:18Z)
Adverse-to-the-eXtreme Panoptic Segmentation: URVIS 2026 Study and Benchmark [61.92065556649544]
The first challenge of its kind, it attracted 17 registered participants and 47 submissions, with 4 teams reaching the final phase.<n>The challenge is based on the MUSES dataset, a multi-sensor benchmark for panoptic segmentation in adverse-to-extreme weather.
arXiv Detail & Related papers (2026-04-18T13:02:51Z)
The Fourth Challenge on Image Super-Resolution ($\ imes$4) at NTIRE 2026: Benchmark Results and Method Overview [202.40386112006652]
The NTIRE 2026 image super-resolution ($times$4) challenge is one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026.<n>The challenge aims to reconstruct high-resolution (HR) images from low-resolution (LR) inputs generated through bicubic downsampling with a $times$4 scaling factor.<n>This report summarizes the challenge design, datasets, evaluation protocol, main results, and methods of participating teams.
arXiv Detail & Related papers (2026-04-16T02:41:53Z)
3rd Workshop on Maritime Computer Vision (MaCVi) 2025: Challenge Results [26.644618344646283]
The 3rd Workshop on Maritime Computer Vision (MaCVi) 2025 addresses maritime computer vision for Unmanned Surface Vehicles (USV) and underwater.<n>This report offers a comprehensive overview of the findings from the challenges.
arXiv Detail & Related papers (2025-01-17T18:34:47Z)
AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and Results [120.95863275142727]
This paper presents the results of the Compressed Video Quality Assessment challenge, held in conjunction with the Advances in Image Manipulation (AIM) workshop at ECCV 2024. The challenge aimed to evaluate the performance of VQA methods on a diverse dataset of 459 videos encoded with 14 codecs of various compression standards.
arXiv Detail & Related papers (2024-08-21T20:32:45Z)
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 [71.80200746293505]
2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV)
arXiv Detail & Related papers (2023-11-23T21:01:14Z)
Recognizing Families In the Wild: White Paper for the 4th Edition Data Challenge [91.55319616114943]
This paper summarizes the supported tasks (i.e., kinship verification, tri-subject verification, and search & retrieval of missing children) in the Recognizing Families In the Wild (RFIW) evaluation. The purpose of this paper is to describe the 2020 RFIW challenge, end-to-end, along with forecasts in promising future directions.
arXiv Detail & Related papers (2020-02-15T02:22:42Z)

This list is automatically generated from the titles and abstracts of the papers in this site.