Research map / Learning theory and algorithms / Matrix and tensor methods
Equiangular Kernel Dictionary Learning With Applications to Dynamic Texture Analysis
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the proposed two-layer kernel sparse-coding descriptor instead of DFS | DT recognition · UCLA-DT Cat-9 | classification accuracy: 97.5 -> 98.6 | Helped |
| Use the proposed two-layer kernel sparse-coding descriptor instead of DFS+ | DT recognition · UCLA-DT SIR | classification accuracy: 74.2 -> 75.8 | Helped |
| Use the proposed two-layer kernel sparse-coding descriptor instead of KGDL | DT recognition · DynTex Alpha | classification accuracy: 86.2 -> 88.8 | Helped |
| Use the proposed two-layer kernel sparse-coding descriptor instead of KGDL | DT recognition · DynTex Beta | classification accuracy: 77.0 -> 77.4 | Helped |
| Use the proposed two-layer kernel sparse-coding descriptor instead of KGDL | DT recognition · DynTex Gamma | classification accuracy: 75.1 -> 75.6 | Helped |
| Use the proposed two-layer kernel sparse-coding descriptor instead of KGDL | DT recognition · DynTex++ | classification accuracy: 92.8 -> 93.4 | Helped |
| Remove the higher-level kernel dictionary representation (ablation) | Two-layer DT descriptor · UCLA-DT Cat-9 and SIR | classification accuracy: 2.8%-3.6 | Hurt |
| Replace the kernel mapping with the identity mapping (ablation) | Two-layer DT descriptor · tested DT datasets | classification accuracy: 2.2%-4.6% | Hurt |
| Use supervised extension (16) for the high-level representation (ablation) | Two-layer DT descriptor · tested DT datasets | classification accuracy | No clear effect |
| Add the label-consistency term to kernel sparse coding | Sparse coding on AR faces · AR face dataset | accuracy: 3.2% | Helped |
Closest papers by meaning
- Understanding l4-based Dictionary Learning: Interpretation, Stability, and Robustness (ICLR 2020 · similarity 0.82)
- Multi-Kernel Low-Rank Dictionary Pair Learning for Multiple Features Based Image Classification (AAAI 2017 · similarity 0.82)
- Online Convolutional Sparse Coding with Sample-Dependent Dictionary (ICML 2018 · similarity 0.82)
- Sparse Coding and Dictionary Learning With Linear Dynamical Systems (CVPR 2016 · similarity 0.82)
- Learned Image Compression with Dictionary-based Entropy Model (CVPR 2025 · similarity 0.81)
- Improved Learning via k-DTW: A Novel Dissimilarity Measure for Curves (ICML 2025 · similarity 0.79)
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