Research map / Detection and segmentation / Open-set and few-shot detection
MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add mask propagation score to motion score (ablation) | MHP-VOS · DAVIS2017 test-dev | Mean: 47.3 -> 52.1 | Helped |
| Increase N-scan pruning from 1 to 3 (ablation) | MHP-VOS · DAVIS2017 test-dev | Mean: 52.1 -> 59.7 | Helped |
| Add multi-object mask merging (ablation) | MHP-VOS · DAVIS2017 test-dev | Mean: 59.7 -> 67.3 | Helped |
| Use proposed gating instead of the comparison gating setup (ablation) | MHP-VOS · DAVIS2017 test-dev | Mean: 67.3 -> 69.5 | Helped |
| Increase N-scan delay from 1 to 3 (ablation) | MHP-VOS · DAVIS2017 | Mean: 62.8 -> 69.5 | Helped |
| Increase N-scan delay from 3 to 5 (ablation) | MHP-VOS · DAVIS2017 | Mean: 69.5 -> 69.7 | Helped |
| Increase N-scan delay from 3 to 5 (ablation) | MHP-VOS · DAVIS2017 | time/frame (s): 14.2 -> 73.6 | Hurt |
| Use MHP-VOS instead of CINM | DAVIS2017 test-dev · DAVIS2017 test-dev | G Mean: 67.5 -> 69.5 | Helped |
| Use MHP-VOS instead of OSVOS-S | DAVIS2016 validation · DAVIS2016 validation | G Mean: 86.6 -> 86.9 | Helped |
| Use MHP-VOS instead of OnAVOS | DAVIS2016 validation · DAVIS2016 validation | J Mean: 86.1 -> 85.7 | Hurt |
Closest papers by meaning
- Learning Dynamic Network Using a Reuse Gate Function in Semi-Supervised Video Object Segmentation (CVPR 2021 · similarity 0.89)
- Learning Fast and Robust Target Models for Video Object Segmentation (CVPR 2020 · similarity 0.89)
- Segment Anything Across Shots: A Method and Benchmark (AAAI 2026 · similarity 0.89)
- Point-VOS: Pointing Up Video Object Segmentation (CVPR 2024 · similarity 0.88)
- Multi-Granularity Video Object Segmentation (AAAI 2025 · similarity 0.88)
- M^3-VOS: Multi-Phase, Multi-Transition, and Multi-Scenery Video Object Segmentation (CVPR 2025 · similarity 0.87)
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