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Main Authors: Zhan, Xinyu, Yang, Lixin, Zhao, Yifei, Mao, Kangrui, Xu, Hanlin, Lin, Zenan, Li, Kailin, Lu, Cewu
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2403.19417
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author Zhan, Xinyu
Yang, Lixin
Zhao, Yifei
Mao, Kangrui
Xu, Hanlin
Lin, Zenan
Li, Kailin
Lu, Cewu
author_facet Zhan, Xinyu
Yang, Lixin
Zhao, Yifei
Mao, Kangrui
Xu, Hanlin
Lin, Zenan
Li, Kailin
Lu, Cewu
contents We present OAKINK2, a dataset of bimanual object manipulation tasks for complex daily activities. In pursuit of constructing the complex tasks into a structured representation, OAKINK2 introduces three level of abstraction to organize the manipulation tasks: Affordance, Primitive Task, and Complex Task. OAKINK2 features on an object-centric perspective for decoding the complex tasks, treating them as a sequence of object affordance fulfillment. The first level, Affordance, outlines the functionalities that objects in the scene can afford, the second level, Primitive Task, describes the minimal interaction units that humans interact with the object to achieve its affordance, and the third level, Complex Task, illustrates how Primitive Tasks are composed and interdependent. OAKINK2 dataset provides multi-view image streams and precise pose annotations for the human body, hands and various interacting objects. This extensive collection supports applications such as interaction reconstruction and motion synthesis. Based on the 3-level abstraction of OAKINK2, we explore a task-oriented framework for Complex Task Completion (CTC). CTC aims to generate a sequence of bimanual manipulation to achieve task objectives. Within the CTC framework, we employ Large Language Models (LLMs) to decompose the complex task objectives into sequences of Primitive Tasks and have developed a Motion Fulfillment Model that generates bimanual hand motion for each Primitive Task. OAKINK2 datasets and models are available at https://oakink.net/v2.
format Preprint
id arxiv_https___arxiv_org_abs_2403_19417
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle OAKINK2: A Dataset of Bimanual Hands-Object Manipulation in Complex Task Completion
Zhan, Xinyu
Yang, Lixin
Zhao, Yifei
Mao, Kangrui
Xu, Hanlin
Lin, Zenan
Li, Kailin
Lu, Cewu
Computer Vision and Pattern Recognition
We present OAKINK2, a dataset of bimanual object manipulation tasks for complex daily activities. In pursuit of constructing the complex tasks into a structured representation, OAKINK2 introduces three level of abstraction to organize the manipulation tasks: Affordance, Primitive Task, and Complex Task. OAKINK2 features on an object-centric perspective for decoding the complex tasks, treating them as a sequence of object affordance fulfillment. The first level, Affordance, outlines the functionalities that objects in the scene can afford, the second level, Primitive Task, describes the minimal interaction units that humans interact with the object to achieve its affordance, and the third level, Complex Task, illustrates how Primitive Tasks are composed and interdependent. OAKINK2 dataset provides multi-view image streams and precise pose annotations for the human body, hands and various interacting objects. This extensive collection supports applications such as interaction reconstruction and motion synthesis. Based on the 3-level abstraction of OAKINK2, we explore a task-oriented framework for Complex Task Completion (CTC). CTC aims to generate a sequence of bimanual manipulation to achieve task objectives. Within the CTC framework, we employ Large Language Models (LLMs) to decompose the complex task objectives into sequences of Primitive Tasks and have developed a Motion Fulfillment Model that generates bimanual hand motion for each Primitive Task. OAKINK2 datasets and models are available at https://oakink.net/v2.
title OAKINK2: A Dataset of Bimanual Hands-Object Manipulation in Complex Task Completion
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2403.19417