ObjectFolder 1.0

OBJECTFOLDER是由斯坦福大学研究人员创建的多模态3D虚拟对象数据集，旨在推动多模态感知与交互研究。该数据集包含100个虚拟化对象，涵盖视觉、听觉和触觉三种模态的隐式神经表示。每个对象通过隐式神经网络建模，可生成不同视角的视觉图像、碰撞声音和表面触觉信息。数据集对象来源于在线资源库，经过精细的视觉纹理处理和物理属性标注。其创建过程结合了神经隐式表示技术，通过深度神经网络编码多模态数据，形成紧凑且高效的对象文件。OBJECTFOLDER可用于多模态对象识别、跨模态检索、3D重建和机器人抓取等任务，为机器学习和机器人技术研究提供标准化测试平台。

OBJECTFOLDER is a multimodal 3D virtual object dataset created by researchers at Stanford University, aimed at advancing research in multimodal perception and interaction. This dataset contains 100 virtualized objects, covering implicit neural representations across three modalities: visual, auditory, and tactile. Each object is modeled with an implicit neural network, and can generate visual images from different viewpoints, collision sounds, and surface tactile information. The objects in the dataset are sourced from online resource libraries, and have undergone fine-grained visual texture processing and physical attribute annotation. Its creation process combines neural implicit representation technologies, encoding multimodal data through deep neural networks to form compact and efficient object files. OBJECTFOLDER can be used for tasks including multimodal object recognition, cross-modal retrieval, 3D reconstruction, and robotic grasping, providing a standardized testbed for machine learning and robotics research.

搜集汇总

背景与挑战

背景概述

ObjectFolder 1.0是一个包含100个虚拟化对象的多感官数据集，每个对象提供视觉、听觉和触觉数据，支持多感官对象识别任务，并采用统一的隐式表示便于使用和共享。