English(EN) Technical Report for the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge: Pretraining-Diverse Ensemble of Foundation Vision Encoders for Robust Outdoor Scene Understanding

视觉编码器集成在ICRA 2026分割挑战赛中获得第二名

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-22 09:57

研究人员为ICRA 2026 GOOSE 2D 精细语义分割挑战赛开发了一种预训练多样化的基础视觉编码器集成。他们的方法将DINOv3、SigLIP2和InternImage等编码器与Mask2Former解码器相结合，并采用了广泛的训练计划和增强技术。该集成在挑战赛中获得第二名，综合mIoU得分达到75.40%，并强调预训练配方是准确性的关键因素，而非模型大小或解码器设计。 AI

影响展示了用于计算机视觉中鲁棒户外场景理解的有效集成技术。

排序理由技术报告，详细介绍了针对特定学术挑战的解决方案。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Zhun Zhong · 2026-06-22 09:57

Technical Report for the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge: Pretraining-Diverse Ensemble of Foundation Vision Encoders for Robust Outdoor Scene Understanding

This report presents our solution for the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge, which requires parsing unstructured outdoor scenes from four camera platforms into 56 fine-grained categories. Our approach pairs foundation vision encoders (including DINOv…

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Technical Report for the ICRA 2026 GOOSE 2D Fine-Grained Semantic Segmentation Challenge: Pretraining-Diverse Ensemble of Foundation Vision Encoders for Robust Outdoor Scene Understanding

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