v1.1.0

BDD100K Models 1.1.0 Release

• Highlights
• New Task: Pose Estimation
• New Models

Highlights

In this release, we provide over 20 pre-trained models for the new pose estimation task in BDD100K, along with evaluation and visualization tools. We also provide over 30 new models for object detection, instance segmentation, semantic segmentation, and drivable area.

New Task: Pose Estimation

With the release of 2D human pose estimation data in BDD100K, we provide pre-trained models in this repo.

• Pose estimation
  • ResNet, MobileNetV2, HRNet, and more.

New Models

We provide additional models for previous tasks

• Object detection
  • Libra R-CNN, HRNet.
• Instance segmentation
  • GCNet, HRNet.
• Semantic segmentation / drivable area
  • NLNet, PointRend.

v1.0.0

BDD100K Models 1.0.0 Release

• Highlights
• Tasks
• Models
• Contribution

Highlights

The model zoo for BDD100K, the largest driving video dataset, is open for business! It contains more than 100 pre-trained models for 7 tasks. Each model also comes with results and visualization on val and test sets. We also provide documentation for community contribution so that everyone can include their models in this repo.

Tasks

We currently support 7 tasks

• Image Tagging
• Object Detection
• Instance Segmentation
• Semantic Segmentation
• Drivable Area
• Multiple Object Tracking (MOT)
• Multiple Object Tracking and Segmentation (MOTS)

Each task includes

• Official evaluation results, model weights, predictions, and visualizations.
• Detailed instructions for evaluation and visualization.

Models

We include popular network models for each task

• Image tagging
  • VGG, ResNet, and DLA.
• Object detection
  • Cascade R-CNN, Sparse R-CNN, Deformable ConvNets v2, and more.
• Instance segmentation
  • Mask R-CNN, Cascade Mask R-CNN, HRNet, and more.
• Semantic segmentation / drivable area
  • Deeplabv3+, CCNet, DNLNet, and more.
• Multiple object tracking (MOT)
  • QDTrack.
• Multiple object tracking and segmentation (MOTS)
  • PCAN.

Contribution

We encourage the BDD100K dataset users to contribute their models to this repo, so that all the info can be used for further result reproduction and analysis. The detailed instruction and model submission template are at the contribution page.