IKEA-Manual: Seeing Shape Assembly Step by Step
This addresses a gap in shape assembly research by providing structured data for AI agents, though it is incremental as it focuses on dataset creation rather than novel methods.
The authors tackled the lack of realistic 3D assembly objects with paired manuals by introducing IKEA-Manual, a dataset of 102 IKEA objects with fine-grained annotations, enabling tasks like assembly plan generation and part segmentation.
Human-designed visual manuals are crucial components in shape assembly activities. They provide step-by-step guidance on how we should move and connect different parts in a convenient and physically-realizable way. While there has been an ongoing effort in building agents that perform assembly tasks, the information in human-design manuals has been largely overlooked. We identify that this is due to 1) a lack of realistic 3D assembly objects that have paired manuals and 2) the difficulty of extracting structured information from purely image-based manuals. Motivated by this observation, we present IKEA-Manual, a dataset consisting of 102 IKEA objects paired with assembly manuals. We provide fine-grained annotations on the IKEA objects and assembly manuals, including decomposed assembly parts, assembly plans, manual segmentation, and 2D-3D correspondence between 3D parts and visual manuals. We illustrate the broad application of our dataset on four tasks related to shape assembly: assembly plan generation, part segmentation, pose estimation, and 3D part assembly.