Project AURIONAI Use-Cases Research & Innovation
PhiGent Robotics
driving

BEVDet

Multi-camera 3D object detection in bird's-eye view, from PhiGent Robotics.

PhiGent RoboticsPhiGent Robotics
Timeline and chart of BEVDet family accuracy versus speed, from the BEVDet README.
Levelmodel
Classdriving
Parametersnot in the notes
Contextnot in the notes
Released22 Dec 2021
Opennessopen source
Runs onmobile or NPU
Statusactive

R&D Topics

Multi-camera bird's-eye-view 3D perceptionexemplar

Identity

Developer
PhiGent Robotics
Family
not in the notes
Released
22 Dec 2021 sourcesannouncement page
Weights published
–
Record checked
12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.

Architecture and Size

Architecture
CNN
Total parameters
– sources
Active parameters
–
Checkpoint parameters
–
Context length
not in the notes
Input
image, sensor
Output
3D
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).

Openness and Access

Openness
open source
Licence
Apache License 2.0 sources
Access routes
open weights download
Where this comes from
The licence file governs over registry tags and aggregator labels.

Deployment

Runs on
mobile or NPU
Footprint
Edge or toolkit builds listed in: Qualcomm AI Hub.
Runtimes
not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.

Indonesia

Indonesian support
not stated
Regional languages
not in the notes
Jakarta hosting
unknown
Languages
not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.

Benchmark Results

The notes record no benchmark result for this model.

Lineage

The notes record no lineage for this model.

Industry Use Cases

No industry use case links this model.

Sources

  1. arxiv.org/abs/2112.11790 https://arxiv.org/abs/2112.11790
  2. github.com/HuangJunJie2017/BEVDet https://github.com/HuangJunJie2017/BEVDet
  3. aihub.qualcomm.com/models/bevdet https://aihub.qualcomm.com/models/bevdet
  4. github.com/HuangJunJie2017/BEVDet https://github.com/HuangJunJie2017/BEVDet/
  5. arxiv.org/html/2112.11790 https://arxiv.org/html/2112.11790

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "BEVDet", https://aurion.semai.id/models/bevdet/, records of October 2026.