BioMTBee: Biologically Constrained Multi-View Template-Based 3D Reconstruction of Bumblebee

Bumblebees play a key role in agriculture, ecology, and bio-inspired robotics, making accurate 3D surface reconstruction essential forquantitative behavioral analysis. However, their dark dense hairs, com-plex structure and flexible limbs prone to visual occlusion and annotationdifficulties, resulting in difficulties in reconstruction. Current template-free or generic template-based models offer limited structural detail andbiological realism, while high-quality bumblebee templates and reliablemorphological priors are lacking. To address these challenges, we pro-pose BioMTBee, a template-based 3D mesh reconstruction frameworkfor bumblebees. We built a high-fidelity articulated mesh template frommicro-CT scans to provide an accurate morphological prior. A multi-view3D pose estimator with spatio-temporal filtering (BPST) is then intro-duced to extract robust 3D keypoints from 2D detections, guiding stablemesh template fitting. Building on this template, we combine 3D poseand shape supervision with biological constraints—bilateral symmetry,kinematic coupling, and temporal smoothness—to achieve anatomicallyconsistent and temporally stable surface reconstructions. Experiments on3D reconstruction from multi-view images show improvements in mor-phological accuracy and biological plausibility over representative base-lines, capturing fast limb movements and fine structural and texturaldetails, and also generalize well to cross-species reconstruction.