Packing and Padding: Coupled Multi-index for Accurate Image Retrieval
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Summary
A coupled Multi-Index (c-MI) framework to perform feature fusion at indexing level, which improves the retrieval accuracy significantly, while consuming only half of the query time compared to the baseline, and is well complementary to many prior techniques.
- Type
- article
- Published
- 2014-02-11
- Cited by
- 223
- References
- 34
- Access
- Open access
- OpenAlex
- https://openalex.org/W2031332477
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:649474
Keywords
Scale-invariant feature transform, Discriminative model, Artificial intelligence, Computer science, Pattern recognition (psychology)
References
- Asymmetric hamming embedding: taking the best of our bits for large scale image search
- Three things everyone should know to improve object retrieval
- Topic Modeling of Multimodal Data: An Autoregressive Approach
- Visual Phraselet: Refining Spatial Constraints for Large Scale Image Search
- The Inverted Multi-Index
- To Aggregate or Not to aggregate: Selective Match Kernels for Image Search
- Bag-of-colors for improved image search
- Object retrieval and localization with spatially-constrained similarity measure and k-NN re-ranking
- Color attributes for object detection
- Scalar quantization for large scale image search
- Unsupervised discovery of co-occurrence in sparse high dimensional data
- Hello neighbor: Accurate object retrieval with k-reciprocal nearest neighbors
- Joint Inverted Indexing
- Context aware topic model for scene recognition
- Improving Bag-of-Features for Large Scale Image Search
- Bayes Merging of Multiple Vocabularies for Scalable Image Retrieval
- Contextual weighting for vocabulary tree based image retrieval
- Spatial coding for large scale partial-duplicate web image search
- Visual Reranking through Weakly Supervised Multi-graph Learning
- Lp-Norm IDF for Large Scale Image Search
Cited by
- Person Re-identification Meets Image Search
- A Probabilistic Analysis of Sparse Coded Feature Pooling and Its Application for Image Retrieval
- Low-rank image tag completion with dual reconstruction structure preserved
- Leveraging coupled multi-index for scalable retrieval of mammographic masses
- Learning Discriminative Feature Representations for Visual Categorization
- Exploitation and Exploration Balanced Hierarchical Summary for Landmark Images
- Heterogeneous Graph Propagation for Large-Scale Web Image Search
- Query-adaptive late fusion for image search and person re-identification
- Attribute-Graph: A Graph Based Approach to Image Ranking
- Unsupervised Local Feature Hashing for Image Similarity Search
- Variable-Weight and Multi-index Similarity Measure for Feature Fusion
- Feature Fusion by Similarity Regression for Logo Retrieval
- BSIFT: Toward Data-Independent Codebook for Large Scale Image Search
- Tensor index for large scale image retrieval
- Image tag completion by low-rank factorization with dual reconstruction structure preserved
- Structure maps based pedestrian detection
- Discovering the Latent Similarities of the KNN Graph by Metric Transformation
- Visual reranking with improved image graph
- Real-time monitoring of television advertisement using BoW
- Coupled Binary Embedding for Large-Scale Image Retrieval
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