most citedSAM2Point: Segment Any 3D as Videos in Zero-shot and Promptable Manners

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cs.CV2024

MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Engines

Dongzhi Jiang, Renrui Zhang, Ziyu Guo +11

The advent of Large Language Models (LLMs) has paved the way for AI search engines, e.g., SearchGPT, showcasing a new paradigm in human-internet interaction. However, most current…

cs.CV20241 cited

SAM2Point: Segment Any 3D as Videos in Zero-shot and Promptable Manners

Ziyu Guo, Renrui Zhang, Xiangyang Zhu +4

We introduce SAM2Point, a preliminary exploration adapting Segment Anything Model 2 (SAM 2) for zero-shot and promptable 3D segmentation. SAM2Point interprets any 3D data as a seri…

cs.CV2024

MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine

Renrui Zhang, Xinyu Wei, Dongzhi Jiang +11

The mathematical capabilities of Multi-modal Large Language Models (MLLMs) remain under-explored with three areas to be improved: visual encoding of math diagrams, diagram-language…

cs.CV20241 cited

No Time to Train: Empowering Non-Parametric Networks for Few-shot 3D Scene Segmentation

Xiangyang Zhu, Renrui Zhang, Bowei He +6

To reduce the reliance on large-scale datasets, recent works in 3D segmentation resort to few-shot learning. Current 3D few-shot segmentation methods first pre-train models on 'see…

cs.CV2023

LiDAR-LLM: Exploring the Potential of Large Language Models for 3D LiDAR Understanding

Senqiao Yang, Jiaming Liu, Ray Zhang +7

Recently, Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) have shown promise in instruction following and 2D image understanding. While these models are p…