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Contrastive Transformation for Self-supervised Correspondence Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add inter-video transformation and intra-inter consistency (ablation) | ContrastCorr · DAVIS-2017 val | J (Mean): 55.8 -> 59.0 | Helped |
| Add inter-video transformation and intra-inter consistency (ablation) | ContrastCorr · DAVIS-2017 val | F (Mean): 60.3 -> 63.7 | Helped |
| Add the inter-video sparsity constraint (ablation) | ContrastCorr with intra- and inter-video transformation · DAVIS-2017 val | J (Mean): 59.0 -> 59.2 | Helped |
| Add the inter-video sparsity constraint (ablation) | ContrastCorr with intra- and inter-video transformation · DAVIS-2017 val | F (Mean): 63.7 -> 64.0 | Helped |
| Add mutual correlation at inference (ablation) | ContrastCorr with intra/inter transformation and sparsity · DAVIS-2017 val | J (Mean): 59.2 -> 60.5 | Helped |
| Add mutual correlation at inference (ablation) | ContrastCorr with intra/inter transformation and sparsity · DAVIS-2017 val | F (Mean): 64.0 -> 65.5 | Helped |
| Use inter-video transformation alone, without intra-video guidance (ablation) | ContrastCorr · DAVIS-2017 val | segmentation performance | Hurt |
Closest papers by meaning
- Joint-task Self-supervised Learning for Temporal Correspondence (NeurIPS 2019 · similarity 0.92)
- Locality-Aware Inter- and Intra-Video Reconstruction for Self-Supervised Correspondence Learning (CVPR 2022 · similarity 0.91)
- Self-Supervised Cross-View Correspondence with Predictive Cycle Consistency (CVPR 2025 · similarity 0.89)
- When the Future Becomes the Past: Taming Temporal Correspondence for Self-supervised Video Representation Learning (CVPR 2025 · similarity 0.86)
- No More Shortcuts: Realizing the Potential of Temporal Self-Supervision (AAAI 2024 · similarity 0.86)
- Emergent Temporal Correspondences from Video Diffusion Transformers (NeurIPS 2025 · similarity 0.86)
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