Apple researchers have created an AI model that reconstructs a 3D object from a single image, while keeping reflections, highlights, and other effects consistent across different viewing angles. Here ...

Abstract: Pseudo points offer dimensional alignment between camera and LiDAR data for multi-modal 3D object detection. However, the pseudo points are irregularly and densely distributed, while LiDAR ...

├── configs/ │ └── pointpillars.yaml │ ├── datasets/ │ └── nuscenes_dataset.py │ ├── models/ │ ├── pointpillars.py │ ├── pillar_encoder.py │ └── losses.py │ ├── utils/ │ ├── voxelization.py │ ├── ...

ResDet3D is a 3D object detection system that uses multi-view images to generate pseudo point clouds via Depth Anything 3 (DA3), then applies teacher-student feature alignment for domain adaptation.

Abstract: Fusion of LiDAR and RGB data has the potential to enhance outdoor 3D object detection accuracy. To address real-world challenges in outdoor 3D object detection, fusion of LiDAR and RGB input ...

We’re introducing SAM 3 and SAM 3D, the newest additions to our Segment Anything Collection, which advance AI understanding of the visual world. SAM 3 enables detection and tracking of objects in ...