Search Results for author: Shupeng Su

Found 6 papers, 5 papers with code

Binary Embedding-based Retrieval at Tencent

1 code implementation17 Feb 2023 Yukang Gan, Yixiao Ge, Chang Zhou, Shupeng Su, Zhouchuan Xu, Xuyuan Xu, Quanchao Hui, Xiang Chen, Yexin Wang, Ying Shan

To tackle the challenge, we propose a binary embedding-based retrieval (BEBR) engine equipped with a recurrent binarization algorithm that enables customized bits per dimension.

Binarization Retrieval

Darwinian Model Upgrades: Model Evolving with Selective Compatibility

no code implementations13 Oct 2022 Binjie Zhang, Shupeng Su, Yixiao Ge, Xuyuan Xu, Yexin Wang, Chun Yuan, Mike Zheng Shou, Ying Shan

The traditional model upgrading paradigm for retrieval requires recomputing all gallery embeddings before deploying the new model (dubbed as "backfilling"), which is quite expensive and time-consuming considering billions of instances in industrial applications.

Face Recognition Retrieval

Privacy-Preserving Model Upgrades with Bidirectional Compatible Training in Image Retrieval

1 code implementation29 Apr 2022 Shupeng Su, Binjie Zhang, Yixiao Ge, Xuyuan Xu, Yexin Wang, Chun Yuan, Ying Shan

The task of privacy-preserving model upgrades in image retrieval desires to reap the benefits of rapidly evolving new models without accessing the raw gallery images.

Image Retrieval Privacy Preserving +1

Towards Universal Backward-Compatible Representation Learning

2 code implementations3 Mar 2022 Binjie Zhang, Yixiao Ge, Yantao Shen, Shupeng Su, Fanzi Wu, Chun Yuan, Xuyuan Xu, Yexin Wang, Ying Shan

The task of backward-compatible representation learning is therefore introduced to support backfill-free model upgrades, where the new query features are interoperable with the old gallery features.

Face Recognition Representation Learning

Deep Joint-Semantics Reconstructing Hashing for Large-Scale Unsupervised Cross-Modal Retrieval

1 code implementation ICCV 2019 Shupeng Su, Zhisheng Zhong, Chao Zhang

Deep cross-modal hashing further improves the retrieval performance as the deep neural networks can generate more semantic relevant features and hash codes.

Cross-Modal Retrieval Retrieval

Greedy Hash: Towards Fast Optimization for Accurate Hash Coding in CNN

2 code implementations NeurIPS 2018 Shupeng Su, Chao Zhang, Kai Han, Yonghong Tian

To convert the input into binary code, hashing algorithm has been widely used for approximate nearest neighbor search on large-scale image sets due to its computation and storage efficiency.

Deep Hashing

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