33 Computer Vision News Computer Vision News What is the outcome: By the submission deadline, 101 participants (43 teams) registered for the TUS-REC2024 Challenge, representing both academia and industry across 14 countries. Six teams, comprising 25 participants, submitted their algorithms (21 valid dockerized solutions) for final evaluation. The submitted methods span a wide range of approaches, including the state space model, the recurrent model, the registrationdriven volume refinement, the attention mechanism, and the physics-informed model. The dataset has been downloaded over 2,300 times to date. All data and code are publicly available to facilitate ongoing development and reproducibility. As a live and evolving benchmark, it is designed to be continuously iterated and improved. The 2025 edition includes more challenging data and continues to grow in scale and impact, drawing 141 individuals (59 teams) across 16 countries so far, consisting of 23 solutions from 7 teams. Key Results & Take-aways: 1) Trackerless reconstruction really works. Multiple teams were able to produce convincing 3D ultrasound volumes without using any external tracking device. This shows that the idea is not just a theoretical concept, but an achievable task under controlled acquisition protocols. 2) Different methods have different strengths. The submitted methods show that there is no single “winning paradigm” yet. Each type of algorithm performed well on some metrics and less well on others, showing that no single technique has emerged as the clear favourite. 3) There is still room for improvement. Our analysis showed that reconstruction quality tends to worsen in longer scans, and current models still struggle to handle a wide variety of scanning patterns. Improving robustness and generalisation remains an important challenge. We welcome interested readers to check out the challenge website and contribute to future developments. Huge thanks to all co-organisers and participants, whose energy and hard work made the challenge possible. TUS-REC Challenge series
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