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Photo Filter Recommendation by Category-Aware Aesthetic Learning
We conduct experiments on the collected FACD for filter recommendation, and the results show that our proposed category-aware aesthetic learning outperforms aesthetic classification methods (e. g., 12% relative improvement).
De-Hashing: Server-Side Context-Aware Feature Reconstruction for Mobile Visual Search
Based on the hashed binary codes, we propose a de-hashing process that reconstructs BoW by leveraging the computing power of remote servers.
Scalable Object Detection by Filter Compression With Regularized Sparse Coding
Our method can reconstruct filters by minimizing score map error, while sparse coding reconstructs filters by minimizing appearance error.
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