wzzheng/TPVFormer

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1364 stars · 127 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

TPVFormer is a CVPR 2023 research implementation of a tri-perspective view transformer for vision-based 3D semantic occupancy prediction, serving as an academic alternative to Tesla's occupancy network. It lifts surround-camera RGB features into 3D space using sparse LiDAR supervision to predict semantic occupancy for all voxels.

Use cases

• predict 3d semantic occupancy from camera images
• research alternative to tesla occupancy network
• segment 3d voxels for autonomous driving scenes
• train occupancy prediction model on nuScenes
• run semantic scene completion on SemanticKITTI
• compare bev vs tri-perspective view perception

When to choose

• you need a published, peer-reviewed baseline for camera-based 3D occupancy prediction
• you want to reproduce CVPR 2023 results on nuScenes or SemanticKITTI
• you are researching vision-centric autonomous driving perception without LiDAR at inference

When to avoid

• you need a production-ready autonomous driving perception stack
• you require dense occupancy prediction rather than a tri-plane representation
• you need actively maintained code with frequent updates

Facets

library · maturity maintenance

machine-learning deep-learning computer-vision image-processing autonomous-vehicles computer-vision deep-learning artificial-intelligence python 3d-occupancy-prediction autonomous-driving bev-perception transformer semantic-segmentation nuscenes cvpr-2023 research-code linux gpu

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markdown · JSON · MCP: product_card(name="wzzheng/TPVFormer")