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Found 3 papers, 2 papers with code
Can 3D Vision-Language Models Truly Understand Natural Language?
To test the language understandability of 3D-VL models, we first propose a language robustness task for systematically assessing 3D-VL models across various tasks, benchmarking their performance when presented with different language style variants.
Beyond Finite Data: Towards Data-free Out-of-distribution Generalization via Extrapolation
Starting with the class of interest, we query the LLMs to extract relevant knowledge for these novel domains.
RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understanding
We propose a lightweight and scalable Regional Point-Language Contrastive learning framework, namely \textbf{RegionPLC}, for open-world 3D scene understanding, aiming to identify and recognize open-set objects and categories.
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