Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

We introduce Cap3D, an automatic approach for generating descriptive text for 3D objects.
This approach utilizes pretrained models from image captioning, image-text alignment, and …

Recent advancements in multimodal pre-training have shown promising efficacy in 3D
representation learning by aligning multimodal features across 3D shapes their 2D …

Abstract In Multimodal Large Language Models (MLLMs) a visual projector plays a crucial
role in bridging pre-trained vision encoders with LLMs enabling profound visual …

Multimodal large language models (MLLMs) have gained significant attention due to their
strong multimodal understanding capability. However existing works rely heavily on modality …

We introduce Point-Bind, a 3D multi-modality model aligning point clouds with 2D image,
language, audio, and video. Guided by ImageBind, we construct a joint embedding space …

Abstract Recent progress in Large Multimodal Models (LMM) has opened up great
possibilities for various applications in the field of human-machine interactions. However …

Abstract Multimodal Large Language Models (MLLMs) have excelled in 2D image-text
comprehension and image generation but their understanding of the 3D world is notably …

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

Leveraging massive knowledge and learning schemes from large language models (LLMs),
recent machine learning models show notable successes in building generalist agents that …