By: Jianren Wang, Xin Wang, Yue Shang-Guan, Abhinav Gupta
This repository is an official implementation of the paper Wanderlust: Online Continual Object Detection in the Real World
TL; DR. Objects Around Krishna (OAK) is a new egocentric video dataset for online continual object detection. We provide a benchmark where the emergence of new object categories follows a pattern similar to what a single person will see in their everyday life.
Abstract. Online continual learning from data streams in dynamic environments is a critical direction in the computer vision field. However, realistic benchmarks and fundamental studies in this line are still missing. To bridge the gap, we present a new online continual object detection benchmark with an egocentric video dataset, Objects Around Krishna (OAK). The emergence of new object categories in our benchmark follows a pattern similar to what a single person might see in their day-to-day life. The dataset also captures the natural distribution shifts as the person travels to different places. These egocentric long running videos provide a realistic playground for continual learning algorithms, especially in online embodied settings.
root
├── object_detection # Object Detection Benchmark
├── detectron2 # Benchmark using Faster RCNN Architecture
└── deformable_detr (coming soon)
├── image_classification (coming soon) # Image Classification Benchmark
├── LICENSE
└── README.md
We provide both the object_detection and image_classification benchmarks using OAK.