OAKINK2: A Dataset of Bimanual Hands-Object Manipulation in Complex Task Completion
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Abstract (arXiv)
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.
Key facts. Cited by 79 papers in the map (data through 13 Oct 2026). Builds on 62 of its 73 references that are in the map. First posted on arXiv 28 Mar 2024.
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50 most cited of 62 All 62 (JSON)
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- 2026TouchSight: Bare-Handed Tactile Prediction from Egocentric Video via Generative Visual Augmentation17 Sep 2026
- 2026ConGraspXL: Controllable Constraint-Conditioned Dexterous Grasping Motion Synthesis14 Sep 2026
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- 2026AdvDex: Learning Dexterous Manipulation from Human Demonstrations via Joint-Aligned Actions and Adversarial Learning14 Aug 2026
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- 2026ACE-Data-0: Human-Centric Ambient Capture as Embodied Data Engine30 Jul 2026
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