Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes
Am I correct in understanding that while the Objectron dataset has Bottles in it, you have only released trained models for Shoes/Chairs/Cups/Cameras? Any pointers on how I could train your model on Bottles? TIA
ahmadyan
commented
2 years ago
Hi,
Am I correct in understanding that while the Objectron dataset has Bottles in it, you have only released trained models for Shoes/Chairs/Cups/Cameras? Any pointers on how I could train your model on Bottles? TIA