# SOLOv2 for instance segmentation ## Introduction - SOLOv2 (Segmenting Objects by Locations) is a fast instance segmentation framework with strong performance. We reproduced the model of the paper, and improved and optimized the accuracy and speed of the SOLOv2.Among them, `Light-R50-VD-DCN-FPN` model reached 38.6 FPS on single Tesla V100, and mask ap on the COCO-val reached 38.8. ## Model Zoo | Backbone | Multi-scale training | Lr schd | Inf time (V100) | Mask AP | Download | Configs | | :---------------------: | :-------------------: | :-----: | :------------: | :-----: | :---------: | :------------------------: | | R50-FPN | False | 1x | 45.7ms | 35.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_r50_fpn_1x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/solov2/solov2_r50_fpn_1x.yml) | | R50-FPN | True | 3x | 45.7ms | 37.9 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_r50_fpn_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/solov2/solov2_r50_fpn_3x.yml) | | R101-VD-FPN | True | 3x | - | 42.6 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_r101_vd_fpn_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/solov2/solov2_r101_vd_fpn_3x.yml) | ## Enhance model | Backbone | Input size | Lr schd | Inf time (V100) | Mask AP | Download | Configs | | :---------------------: | :-------------------: | :-----: | :------------: | :-----: | :---------: | :------------------------: | | Light-R50-VD-DCN-FPN | 512 | 3x | 25.9ms | 38.8 | [model](https://paddlemodels.bj.bcebos.com/object_detection/solov2_light_r50_vd_fpn_dcn_512_3x.pdparams) | [config](https://github.com/PaddlePaddle/PaddleDetection/tree/master/configs/solov2/solov2_light_r50_vd_fpn_dcn_512_3x.yml) | ## Citations ``` @article{wang2020solov2, title={SOLOv2: Dynamic, Faster and Stronger}, author={Wang, Xinlong and Zhang, Rufeng and Kong, Tao and Li, Lei and Shen, Chunhua}, journal={arXiv preprint arXiv:2003.10152}, year={2020} } ```