awesome-cbir
Awesome lists to CNN based Image Retrieval Projects an Papers
https://github.com/offbye/awesome-cbir
Last synced: 1 day ago
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- Visual Categorization with Bags of Keypoints
- Revisiting the VLAD image representation
- Image Classification with the Fisher Vector: Theory and Practice
- Combining Fisher Vector and Convolutional Neural Networks for Image Retrieval
- Local Descriptors Optimized for Average Precision
- Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking
- Fast Spectral Ranking for Similarity Search - aiki/manifold-diffusion), CVPR 2018
- Object retrieval with large vocabularies and fast spatial matching
- ORB: an efficient alternative to SIFT or SURF
- Three things everyone should know to improve object retrieval
- On-the-fly learning for visual search of large-scale image and video datasets
- Improving the Fisher Kernel for Large-Scale Image Classification
- Efficient Large-scale Image Search With a Vocabulary Tree
- Deep Image Retrieval:Learning Global Representations for Image search
- End-to-end Learning of Deep Visual Representations for Image retrieval
- What Is the Best Practice for CNNs Applied to Visual Instance Retrieval?
- Faster R-CNN Features for Instance Search
- Cross-dimensional Weighting for Aggregated Deep Convolutional Features
- Class-Weighted Convolutional Features for Image Retrieval
- Aggregating Deep Convolutional Features for Image Retrieval
- Particular object retrieval with integral max-pooling of CNN activations
- Particular object retrieval using CNN
- Learning to Match Aerial Images with Deep Attentive Architectures
- Siamese Network of Deep Fisher-Vector Descriptors for Image Retrieval
- Fine-tuning CNN Image Retrieval with No Human Annotation
- Regional Attention Based Deep Feature for Image Retrieval - RegionalAttention), BMVC 2018.
- Learning Discriminative Affine Regions via Discriminability - aiki/affnet)
- A Large Dataset for Improving Patch Matching - Dataset](https://github.com/rmitra/PS-Dataset)
- LF-Net: Learning Local Features from Images
- SuperPoint: Self-Supervised Interest Point Detection and Description
- Learning a Complete Image Indexing Pipeline
- Object Recognition from Local Scale-Invariant Features
- Selective Deep Convolutional Features for Image Retrieval
- An accurate retrieval through R-MAC+ descriptors for landmark recognition
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