tao▌

PointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a

SegFormer for semantic segmentation. Lightweight transformer-based architecture with hierarchical feature

Four-step image referring-expression pipeline: turns images plus KITTI bounding-box labels into region

OCDNet for scene text detection. Detects arbitrary-oriented text regions in natural images using a

Run `tao-daft convert` to convert NVIDIA TAO DAFT datasets between supported formats. Do not use for non-DAFT data.

NVPanoptix3D for panoptic 3D scene reconstruction from posed RGB images. Produces 3D panoptic segmentation

NVDINOv2 for self-supervised visual representation learning. Trains vision transformers via self-distillation

Metric-learning recognition (ml-recog) for fine-grained visual recognition. Learns embeddings for

Mask2Former for universal image segmentation (panoptic, instance, and semantic). Transformer-based with

Mask Grounding DINO for grounded instance segmentation. Extends Grounding DINO with a mask-prediction head for