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Found 3 papers, 3 papers with code
M3DBench: Let's Instruct Large Models with Multi-modal 3D Prompts
Furthermore, we establish a new benchmark for assessing the performance of large models in understanding multi-modal 3D prompts.
LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planning
However, developing LMMs that can comprehend, reason, and plan in complex and diverse 3D environments remains a challenging topic, especially considering the demand for understanding permutation-invariant point cloud 3D representations of the 3D scene.
Vote2Cap-DETR++: Decoupling Localization and Describing for End-to-End 3D Dense Captioning
Moreover, we argue that object localization and description generation require different levels of scene understanding, which could be challenging for a shared set of queries to capture.
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