分割一切并不够,还要3D重建一切,SAM 3D来了

Core Viewpoint - Meta has launched significant updates with the introduction of SAM 3D and SAM 3, enhancing the understanding of images in 3D and providing advanced capabilities for object detection, segmentation, and tracking in images and videos [2][6][40]. Group 1: SAM 3D Overview - SAM 3D is the latest addition to the SAM series, featuring two models: SAM 3D Objects and SAM 3D Body, both demonstrating state-of-the-art performance in converting 2D images into detailed 3D reconstructions [2][4]. - SAM 3D Objects allows users to generate 3D models from a single image, overcoming limitations of traditional 3D modeling that often relies on isolated or synthetic data [11][15]. - Meta has annotated nearly 1 million real-world images, generating approximately 3.14 million 3D meshes, utilizing a scalable data engine to enhance the quality and quantity of 3D data [20][26]. Group 2: SAM 3D Body - SAM 3D Body focuses on accurate 3D human pose and shape reconstruction from single images, maintaining high-quality performance even in complex scenarios with occlusions and unusual poses [28][30]. - The model is interactive, allowing users to guide and control predictions, enhancing accuracy and usability [29]. - A high-quality training dataset of around 8 million images was created to improve the model's performance across various 3D benchmarks [33]. Group 3: SAM 3 Capabilities - SAM 3 introduces promptable concept segmentation, enabling the model to detect and segment specific concepts based on text or example image prompts, significantly improving its performance in concept recognition [40][42]. - The architecture of SAM 3 builds on previous advancements, utilizing components like the Meta Perception Encoder and DETR for enhanced image recognition and object detection capabilities [42][44]. - SAM 3 achieves a twofold increase in cgF1 scores for concept recognition and maintains near real-time performance for images with over 100 detection targets, completing inference in approximately 30 milliseconds on H200 GPUs [44].