Yuk Heo, Yeong Jun Koh, Chang-Su Kim
We propose a novel guided interactive segmentation (GIS) algorithm for video objects to improve the segmentation accuracy and reduce the interaction time. First, we design the reliability-based attention module to analyze the reliability of multiple annotated frames. Second, we develop the intersection-aware propagation module to propagate segmentation results to neighboring frames. Third, we introduce the GIS mechanism for a user to select unsatisfactory frames quickly with less effort. Experimental results demonstrate that the proposed algorithm provides more accurate segmentation results at a faster speed than conventional algorithms. Codes are available at https://github.com/yuk6heo/GIS-RAmap.
| Task | Dataset | Metric | Value | Model |
|---|---|---|---|---|
| Video | DAVIS 2017 | AUC-J | 0.82 | GIS |
| Video | DAVIS 2017 | AUC-J&F | 0.856 | GIS |
| Video | DAVIS 2017 | J&F@60s | 0.866 | GIS |
| Video | DAVIS 2017 | J@60s | 0.829 | GIS |
| Video Object Segmentation | DAVIS 2017 | AUC-J | 0.82 | GIS |
| Video Object Segmentation | DAVIS 2017 | AUC-J&F | 0.856 | GIS |
| Video Object Segmentation | DAVIS 2017 | J&F@60s | 0.866 | GIS |
| Video Object Segmentation | DAVIS 2017 | J@60s | 0.829 | GIS |