Visual Question Answering (VQA) on 3D MM-Vet

Metric: Overall Accuracy (higher is better)

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#	Model↕	Overall Accuracy▼	Extra Data	Paper	Date↕	Code
1	ShapeLLM-13B	53.1	No	ShapeLLM: Universal 3D Object Understanding for ...	2024-02-27	Code
2	ShapeLLM-7B	47.4	No	ShapeLLM: Universal 3D Object Understanding for ...	2024-02-27	Code
3	PointLLM-13B v1.2	46.6	No	PointLLM: Empowering Large Language Models to Un...	2023-08-31	Code
4	PointLLM-7B v1.2	41.2	No	PointLLM: Empowering Large Language Models to Un...	2023-08-31	Code
5	Point-Bind & Point-LLM	23.5	No	Point-Bind & Point-LLM: Aligning Point Cloud wit...	2023-09-01	Code

#1ShapeLLM-13BSOTA
53.1
Overall Accuracy· 2024-02-27
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction Code
#2ShapeLLM-7B
47.4
Overall Accuracy· 2024-02-27
ShapeLLM: Universal 3D Object Understanding for Embodied Interaction Code
#3PointLLM-13B v1.2SOTA
46.6
Overall Accuracy· 2023-08-31
PointLLM: Empowering Large Language Models to Understand Point Clouds Code
#4PointLLM-7B v1.2
41.2
Overall Accuracy· 2023-08-31
PointLLM: Empowering Large Language Models to Understand Point Clouds Code
#5Point-Bind & Point-LLM
23.5
Overall Accuracy· 2023-09-01
Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following Code