BEVFusion for multi-sensor 3D object detection. Fuses LiDAR point clouds and camera images in bird's-eye-view (BEV) space, used in autonomous driving for robust 3D perception. Use when training, evaluating, or running inference for a TAO BEVFusion model. Trigger phrases include "train BEVFusion", "LiDAR + camera fusion", "BEV 3D detection", "multi-sensor 3D perception".
Install
npx skills add NVIDIA/skills --skill tao-train-bevfusionnpx skills add NVIDIA/skills --skill tao-train-bevfusion -a claude-code -gnpx skills add NVIDIA/skills --skill tao-train-bevfusion -a codex -ggemini skills install https://github.com/NVIDIA/skills.git --path skills/tao-train-bevfusiongh skill install NVIDIA/skills tao-train-bevfusiongit clone --depth 1 https://github.com/NVIDIA/skills /tmp/NVIDIA__skills
mkdir -p ~/.claude/skills ~/.agents/skills
cp -R /tmp/NVIDIA__skills/skills/tao-train-bevfusion ~/.claude/skills/tao-train-bevfusion # Claude Code
cp -R /tmp/NVIDIA__skills/skills/tao-train-bevfusion ~/.agents/skills/tao-train-bevfusion # Codex, Cursor, Gemini CLI, Copilot, OpenCode