MonoArt: Progressive Structural Reasoning for Monocular Articulated 3D Reconstruction

Summary

MonoArt is a unified framework for monocular articulated 3D reconstruction built on progressive structural reasoning, presented by Haitian Li, Haozhe Xie, and Junxiang Xu in an arXiv paper (2503.16922). Instead of predicting articulation parameters directly from image features, MonoArt progressively transforms visual observations into canonical geometry, structured part representations, and motion-aware embeddings within a single architecture. This staged reasoning pipeline allows the model to first recover reliable geometry and part structure before inferring articulated motion, leading to more accurate and robust predictions from a single image. According to the post, MonoArt achieves state-of-the-art performance on the PartNet-Mobility benchmark in both reconstruction accuracy and inference speed. The post shares the paper overview, author list, arXiv link, and both a Chinese and the original English abstract for readers following computer vision research on articulated object reconstruction.