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NetVLAD is a deep learning-based image descriptor framework developed by Relja Arandjelović for place recognition and image retrieval. It extends standard CNNs with a trainable VLAD (Vector of Locally Aggregated Descriptors) layer to create compact, robust global descriptors from image features. This implementation includes training code and pretrained models using the Pittsburgh and Tokyo datasets.
Features
- Trainable VLAD layer integrated into CNNs
- High-performance place recognition and retrieval
- Pretrained models and benchmark support
- PyTorch/Torch7-based implementations
- Evaluation scripts on standard datasets
- Includes feature extraction and descriptor matching
Project Samples
Categories
Computer Vision LibrariesLicense
MIT LicenseFollow Netvlad
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