# Efficiently Collecting Training Dataset for 2D Object Detection by Online Visual Feedback

arXiv: https://arxiv.org/abs/2304.04901 · HTML: https://mlsanity.com/paper/2304.04901/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 45 references that are in the map.
- First posted on arXiv 11 Apr 2023.

## Builds on (most cited first, 7 of 7)

- [EfficientDet: Scalable and Efficient Object Detection](https://mlsanity.com/paper/1911.09070/) (2019)
- [The VIA Annotation Software for Images, Audio and Video](https://mlsanity.com/paper/1904.10699/) (2019)
- [Large-scale interactive object segmentation with human annotators](https://mlsanity.com/paper/1903.10830/) (2019)
- [EasyLabel: A Semi-Automatic Pixel-wise Object Annotation Tool for Creating Robotic RGB-D Datasets](https://mlsanity.com/paper/1902.01626/) (2019)
- [The 6th AI City Challenge](https://mlsanity.com/paper/2204.10380/) (2022)
- [Semi-Automatic Labeling for Deep Learning in Robotics](https://mlsanity.com/paper/1908.01862/) (2019)
- [Robotic Waste Sorter with Agile Manipulation and Quickly Trainable Detector](https://mlsanity.com/paper/2104.01260/) (2021)

## Abstract (arXiv)

Training deep-learning-based vision systems require the manual annotation of a significant number of images. Such manual annotation is highly time-consuming and labor-intensive. Although previous studies have attempted to eliminate the effort required for annotation, the effort required for image collection was retained. To address this, we propose a human-in-the-loop dataset collection method that uses a web application. To counterbalance the workload and performance by encouraging the collection of multi-view object image datasets in an enjoyable manner, thereby amplifying motivation, we propose three types of online visual feedback features to track the progress of the collection status. Our experiments thoroughly investigated the impact of each feature on collection performance and quality of operation. The results suggested the feasibility of annotation and object detection.