Research map / Label-efficient and robust learning / Zero-/few-shot and meta-learning
Matrix Tri-Factorization With Manifold Regularizations for Zero-Shot Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add joint test-time manifold prediction (ablation) | MFMR · aPY, AwA, CUB, and SUN | accuracy (%): 48.2 -> 56.8; 79.8 -> 83.5; 47.7 -> 53.6; 84.0 -> 84.5 | Helped |
| add joint test-time manifold prediction (ablation) | MFMR · aPY, AwA, CUB, and SUN | mAP (%): 45.6 -> 55.9; 70.8 -> 82.8; 30.6 -> 47.5; 77.4 -> 83.2 | Helped |
| add joint test-time manifold prediction (ablation) | MFMR · AwA generalized ZSL | U → T accuracy: 13.4 -> 18.4 | Helped |
| vary manifold regularization coefficient λ (ablation) | MFMR and MFMR-joint · AwA and CUB | accuracy (%) | Mixed |
| vary neighborhood parameter k (ablation) | MFMR and MFMR-joint · AwA and CUB | accuracy (%) | Mixed |
| increase test-instance manifold coefficient γ (ablation) | MFMR-joint · AwA and CUB | accuracy (%) | Helped |
Closest papers by meaning
- Zero-Shot Recognition Using Dual Visual-Semantic Mapping Paths (CVPR 2017 · similarity 0.89)
- Synthesized Classifiers for Zero-Shot Learning (CVPR 2016 · similarity 0.88)
- Zero Shot Learning with the Isoperimetric Loss (AAAI 2020 · similarity 0.88)
- TPR: Topology-Preserving Reservoirs for Generalized Zero-Shot Learning (NeurIPS 2024 · similarity 0.87)
- Epsilon: Exploring Comprehensive Visual-Semantic Projection for Multi-Label Zero-Shot Learning (AAAI 2025 · similarity 0.86)
- ZeroDiff: Solidified Visual-semantic Correlation in Zero-Shot Learning (ICLR 2025 · similarity 0.86)
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