Research map / Detection and segmentation / CNN features
Learning to Learn Better for Video Object Segmentation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace JOINT mask-based guidance and direct branch summation with DLGM and adaptive gated fusion | JOINT · DAVIS 2017 val | J & F: 83.5 -> 84.6 | Helped |
| replace JOINT with LLB | JOINT · YouTube-VOS 2018 val | G: 83.1 -> 83.8 | Helped |
| replace JOINT with LLB | JOINT · YouTube-VOS 2019 val | G: 82.8 -> 83.6 | Helped |
| add DLGM without AFM (ablation) | JOINT · DAVIS 2017 val | J & F: 83.5 -> 84.2 | Helped |
| add AFM without DLGM (ablation) | JOINT · DAVIS 2017 val | J & F: 83.5 -> 83.8 | Helped |
| add DLGM and AFM together (ablation) | JOINT · DAVIS 2017 val | J & F: 83.5 -> 84.6 | Helped |
| replace mask input with BFF while retaining the 5-layer CNN encoder (ablation) | JOINT with AFM · DAVIS 2017 val | J & F: 83.8 -> 84.1 | Helped |
| replace the 5-layer CNN with ViTAE-6M while retaining mask input (ablation) | JOINT with AFM · DAVIS 2017 val | J & F: 83.8 -> 83.9 | No clear effect |
| use BFF input and ViTAE-6M encoder together (ablation) | JOINT with AFM · DAVIS 2017 val | J & F: 83.8 -> 84.6 | Helped |
Closest papers by meaning
- A Transductive Approach for Video Object Segmentation (CVPR 2020 · similarity 0.89)
- From ViT Features to Training-free Video Object Segmentation via Streaming-data Mixture Models (NeurIPS 2023 · similarity 0.88)
- Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentation (CVPR 2023 · similarity 0.88)
- Learning Dynamic Network Using a Reuse Gate Function in Semi-Supervised Video Object Segmentation (CVPR 2021 · similarity 0.87)
- Learning Spatial-Semantic Features for Robust Video Object Segmentation (ICLR 2025 · similarity 0.87)
- LiVOS: Light Video Object Segmentation with Gated Linear Matching (CVPR 2025 · similarity 0.86)
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