| # 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](https://bj.bcebos.com/v1/paddledet/models/queryinst_r50_fpn_1x_pro100_coco.pdparams) | [config](./queryinst_r50_fpn_1x_pro100_coco.yml) | | |
| | ResNet50-FPN | 3x | 300 | √ | √ | 47.9 | 42.1 | [model](https://bj.bcebos.com/v1/paddledet/models/queryinst_r50_fpn_ms_crop_3x_pro300_coco.pdparams) | [config](./queryinst_r50_fpn_ms_crop_3x_pro300_coco.yml) | | |
| - COCO val-set evaluation results. | |
| - These configurations are for 4-card training. | |
| Please modify these parameters as appropriate: | |
| ```yaml | |
| 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} | |
| } | |
| ``` | |