Description: GPT4Point
Multimodal Large Language Models (MLLMs) have excelled in 2D image-text comprehension and image generation, but their understanding of the 3D world is notably deficient, limiting progress in 3D language understanding and generation. To solve this problem, we introduce GPT4Point, an innovative groundbreaking point-language multimodal model designed specifically for unified 3D object understanding and generation within the MLLM framework . GPT4Point as a powerful 3D MLLM seamlessly can execute a variety of po
Unified Framework for Point-language Understanding and Generation. We present the unified framework for point-language understanding and generation GPT4Point, including the 3D MLLM for point-text tasks and controlled 3D generation . Automated Point-language Dataset Annotation Engine Pyramid-XL. We introduce the automated point-language dataset annotation engine Pyramid-XL based on Objaverse-XL, currently encompassing 1M pairs of varying levels of coarseness and can be extended cost-effectively. Object-level
Task examples of GPT4Point. It performs accurate 3D recognition, detailed captioning, precise Q&A, and high-quality controllable 3D generation. Additionally, GPT4Point excels in 3D anomalous object description, accurately assessing abnormal shapes like the multi-face object and the 3D generation failure case. It is a crucial ability in the assessment of generated 3D objects.