QueryInst: Instances as Queries
Introduction
QueryInst is a multi-stage end-to-end system that treats instances of interest as learnable queries, enabling query based object detectors, e.g., Sparse R-CNN, to have strong instance segmentation performance. The attributes of instances such as categories, bounding boxes, instance masks, and instance association embeddings are represented by queries in a unified manner. In QueryInst, a query is shared by both detection and segmentation via dynamic convolutions and driven by parallelly-supervised multi-stage learning.
Model Zoo
| Backbone | Lr schd | Proposals | MultiScale | RandomCrop | bbox AP | mask AP | Download | Config |
|---|---|---|---|---|---|---|---|---|
| ResNet50-FPN | 1x | 100 | × | × | 42.1 | 37.8 | model | config |
| ResNet50-FPN | 3x | 300 | √ | √ | 47.9 | 42.1 | model | config |
- COCO val-set evaluation results.
- These configurations are for 4-card training.
Please modify these parameters as appropriate:
worker_num: 4
TrainReader:
use_shared_memory: true
find_unused_parameters: true
Citations
@InProceedings{Fang_2021_ICCV,
author = {Fang, Yuxin and Yang, Shusheng and Wang, Xinggang and Li, Yu and Fang, Chen and Shan, Ying and Feng, Bin and Liu, Wenyu},
title = {Instances As Queries},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2021},
pages = {6910-6919}
}