Luojie Yang — accepted AI-conference papers

2026

Learning a Unified Latent Action Space from Videos with Action-centric Cycle Consistency

Guangyan Chen, Qi Shao, Te Cui, Zichen Zhou, Weixin Mao, Luojie Yang +4

CVPR 2026

Video data provides a rich source beyond expensive action-labeled data for advancing robot learning. Recent approaches have demonstrated promising potential in leveraging video data by learning latent actions for policy training. The latent action tokenizer encodes latent actions between successive

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2025

Open-RGBT: Open-Vocabulary RGB-T Zero-Shot Semantic Segmentation in Open-World Environments

Meng Yu, Yufeng Yue, Luojie Yang, Xunjie He, Yi Yang, Mengyin Fu

ICRA 2025

Semantic segmentation is a critical technique for effective scene understanding. Traditional RGB-T semantic segmentation models often struggle to generalize across diverse scenarios due to their reliance on pretrained models and predefined categories. Recent advancements in Visual Language Models (V

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