OpenMMLab Detection Toolbox and Benchmark
https://mmdetection.readthedocs.io/
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3.2 KiB
3.2 KiB
SOLO: Segmenting Objects by Locations
Introduction
@inproceedings{wang2020solo,
title = {{SOLO}: Segmenting Objects by Locations},
author = {Wang, Xinlong and Kong, Tao and Shen, Chunhua and Jiang, Yuning and Li, Lei},
booktitle = {Proc. Eur. Conf. Computer Vision (ECCV)},
year = {2020}
}
Results and Models
SOLO
| Backbone | Style | MS train | Lr schd | Mem (GB) | Inf time (fps) | mask AP | Download |
|---|---|---|---|---|---|---|---|
| R-50 | pytorch | N | 1x | 8.0 | 14.0 | 33.1 | model | log |
| R-50 | pytorch | Y | 3x | 7.4 | 14.0 | 35.9 | model | log |
Decoupled SOLO
| Backbone | Style | MS train | Lr schd | Mem (GB) | Inf time (fps) | mask AP | Download |
|---|---|---|---|---|---|---|---|
| R-50 | pytorch | N | 1x | 7.8 | 12.5 | 33.9 | model | log |
| R-50 | pytorch | Y | 3x | 7.9 | 12.5 | 36.7 | model | log |
- Decoupled SOLO has a decoupled head which is different from SOLO head. Decoupled SOLO serves as an efficient and equivalent variant in accuracy of SOLO. Please refer to the corresponding config files for details.
Decoupled Light SOLO
| Backbone | Style | MS train | Lr schd | Mem (GB) | Inf time (fps) | mask AP | Download |
|---|---|---|---|---|---|---|---|
| R-50 | pytorch | Y | 3x | 2.2 | 31.2 | 32.9 | model | log |
- Decoupled Light SOLO using decoupled structure similar to Decoupled SOLO head, with light-weight head and smaller input size, Please refer to the corresponding config files for details.