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Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy

arXiv 2408.04940 ↗First posted 9 Aug 2024cs.CVcited by 16

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Abstract (arXiv)

We present the Capsule Vision 2024 Challenge: Multi-Class Abnormality Classification for Video Capsule Endoscopy. It was virtually organized by the Research Center for Medical Image Analysis and Artificial Intelligence (MIAAI), Department of Medicine, Danube Private University, Krems, Austria in collaboration with the 9th International Conference on Computer Vision & Image Processing (CVIP 2024) being organized by the Indian Institute of Information Technology, Design and Manufacturing (IIITDM) Kancheepuram, Chennai, India. This document provides an overview of the challenge, including the registration process, rules, submission format, description of the datasets used, qualified team rankings, all team descriptions, and the benchmarking results reported by the organizers.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 0 of its 42 references that are in the map. First posted on arXiv 9 Aug 2024.

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Citing papers per year: 2024: 13; 2025: 1; 2026: 2.

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  1. 2024Frontiers in Intelligent Colonoscopycited by 13
  2. 2026M3CoTBench: Benchmark Chain-of-Thought of MLLMs in Medical Image Understandingcited by 6
  3. 2024Capsule Endoscopy Multi-classification via Gated Attention and Wavelet Transformationscited by 2
  4. 2024Domain-Adaptive Pre-training of Self-Supervised Foundation Models for Medical Image Classification in Gastrointestinal Endoscopycited by 2
  5. 2024CASCRNet: An Atrous Spatial Pyramid Pooling and Shared Channel Residual based Network for Capsule Endoscopycited by 1
  6. 2024Integrating Deep Feature Extraction and Hybrid ResNet-DenseNet Model for Multi-Class Abnormality Detection in Endoscopic Imagescited by 1
  7. 2024CapsoNet: A CNN-Transformer Ensemble for Multi-Class Abnormality Detection in Video Capsule Endoscopycited by 1
  8. 2024CapsuleNet: A Deep Learning Model To Classify GI Diseases Using EfficientNet-b7cited by 1
  9. 2024A Multimodal Approach For Endoscopic VCE Image Classification Using BiomedCLIP-PubMedBERTcited by 1
  10. 2024CAVE-Net: Classifying Abnormalities in Video Capsule Endoscopycited by 1
  11. 2024Exploring Self-Supervised Learning with U-Net Masked Autoencoders and EfficientNet-B7 for Improved Gastrointestinal Abnormality Classification in Video Capsule Endoscopycited by 0
  12. 2024Multi-Class Abnormality Classification Task in Video Capsule Endoscopycited by 0
4 more
  1. 2024Capsule Vision Challenge 2024: Multi-Class Abnormality Classification for Video Capsule Endoscopycited by 0
  2. 2024FUSECAPS: Investigating Feature Fusion Based Framework for Capsule Endoscopy Image Classificationcited by 0
  3. 2025EndoCIL: A Class-Incremental Learning Framework for Endoscopic Image Classificationcited by 0
  4. 2026Benchmarking the Domain Gap: Model Selection Instability Under Domain Shift in Video Capsule Endoscopycited by 0