The Hierarchical Attention Mechanism is the key technical component of PartCrafter to realize high-quality multi-part generation. The mechanism solves the two major pain points of traditional methods by establishing a three-level attention network (whole-object-part): on the one hand, the global attention layer ensures style coordination among different objects (e.g., material consistency of tables and chairs); on the other hand, the local attention layer accurately controls the details at the part level (e.g., the exact location of screw holes). Experimental data show that this layered design improves the part assembly accuracy of the generated model by 371 TP3T, while the semantic rationality in complex scenes (containing more than 5 related objects) reaches 911 TP3T. Typical applications include generating stylistically consistent furniture sets from a single interior photo, and reconstructing assembled part systems from pictures of mechanical devices.
This answer comes from the articlePartCrafter: Generating Editable 3D Part Models from a Single ImageThe
