3D-RE-GEN reconstructs complete editable 3D indoor scenes from a single RGB photo. It integrates SAM, Hunyuan3D-2.0, and VGGT models in a modular Python pipeline.
SAM3-UNet adapts Meta’s SAM3 foundation model for dense prediction tasks using a parameter-efficient adapter and U-Net decoder, enabling training under 6 GB GPU memory.
Medical-SAM3 adapts the SAM3 foundation model for universal prompt-driven medical image segmentation, offering pretrained weights and evaluation tools on diverse medical datasets.
Tencent’s Hunyuan3D-Part offers a two-model pipeline for 3D mesh part segmentation with P3-SAM and high-fidelity part generation via X-Part, targeting semantic mesh decomposition.
