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New dataset enables visibility analysis in Dota 2 matches

Researchers have developed a new dataset and methodology for analyzing visibility in Dota 2 matches, moving beyond traditional structured data. The Dota2-Vis dataset, derived from The International 2025 matches, includes video footage and annotated minimap images. By employing object detection models like YOLO11l, the system estimates player presence and visibility, revealing behavioral patterns not easily captured by existing analytics. AI

IMPACT Enables deeper analysis of player behavior and strategy in esports through computer vision.

RANK_REASON The cluster contains an academic paper detailing a new dataset and methodology for computer vision analysis in a specific domain (esports analytics).

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New dataset enables visibility analysis in Dota 2 matches

COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Ricardo da Rocha Carvalho, Elo\'isa Oliveira, Luiz Bernardo Martins Kummer, Emerson Cabrera Paraiso, Rayson Laroca ·

    Computer Vision for MOBA Analytics: A Dataset and Baseline for Visibility Analysis in Dota 2

    arXiv:2606.26970v1 Announce Type: new Abstract: Introduction: Most Multiplayer Online Battle Arena (MOBA) analytics studies rely on structured data, which does not directly capture what each team could actually see during a match. Objective: This work introduces Dota2-Vis, a vide…

  2. arXiv cs.CV TIER_1 English(EN) · Rayson Laroca ·

    Computer Vision for MOBA Analytics: A Dataset and Baseline for Visibility Analysis in Dota 2

    Introduction: Most Multiplayer Online Battle Arena (MOBA) analytics studies rely on structured data, which does not directly capture what each team could actually see during a match. Objective: This work introduces Dota2-Vis, a video-based dataset, and a baseline pipeline for vis…