Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
- scaled-yolov4
- yolor
- yolov3
- yolov4
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[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
- object-detection
- open-world
- open-world-detection
- vision-language
PyTorch implementation of YOLOv3, YOLOv3-SPP, and YOLOv3-tiny for real-time object detection with training, validation, inference, and multi-format export.
tensorflow implementation of 'YOLO : Real-Time Object Detection'
Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)
- 3d-object-detection
- lidar-point-cloud
- bevmap
- center
Tiny YOLO for iOS implemented using CoreML but also using the new MPS graph API.
- core-ml
- mps
- metal
- machine-learning
Official implementation of Joint Monocular 3D Vehicle Detection and Tracking (ICCV 2019)
- 3d-tracking
- 3d-estimation
- monocular-3d-detection
- monocular-vehicle-tracking
YOLOv5 - most advanced vision AI model for object detection. Natively implemented in PyTorch and exportable to TFLite for use in edge solutions.
Implementation of the Mask R-CNN model using OCaml's numerical library Owl.