Large-Scale Visual Search with Binary Distributed Graph at Alibaba
Kang Zhao, Pan Pan, Yun Zheng, Yanhao Zhang, Changxu Wang, Yingya, Zhang, Yinghui Xu, Rong Jin

TL;DR
This paper introduces a Binary Distributed Graph algorithm for large-scale visual search, enabling rapid offline graph construction and efficient online retrieval on billions of images, outperforming existing methods.
Contribution
It presents a novel binary code-based graph construction method optimized for distributed systems, significantly improving scalability and speed for billion-scale visual search.
Findings
Builds a billion-scale graph in hours
Achieves comparable performance to real-value methods
Outperforms state-of-the-art in large-scale experiments
Abstract
Graph-based approximate nearest neighbor search has attracted more and more attentions due to its online search advantages. Numbers of methods studying the enhancement of speed and recall have been put forward. However, few of them focus on the efficiency and scale of offline graph-construction. For a deployed visual search system with several billions of online images in total, building a billion-scale offline graph in hours is essential, which is almost unachievable by most existing methods. In this paper, we propose a novel algorithm called Binary Distributed Graph to solve this problem. Specifically, we combine binary codes with graph structure to speedup online and offline procedures, and achieve comparable performance with the ones in real-value based scenarios by recalling more binary candidates. Furthermore, the graph-construction is optimized to completely distributed…
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