3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.CV2022
Darwinian Model Upgrades: Model Evolving with Selective Compatibility
Binjie Zhang, Shupeng Su, Yixiao Ge +5
The traditional model upgrading paradigm for retrieval requires recomputing all gallery embeddings before deploying the new model (dubbed as "backfilling"), which is quite expensiv…
cs.CV2022★ 3 cited
Privacy-Preserving Model Upgrades with Bidirectional Compatible Training in Image Retrieval
Shupeng Su, Binjie Zhang, Yixiao Ge +4
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. A pioneering…
cs.CV2022
Towards Universal Backward-Compatible Representation Learning
Binjie Zhang, Yixiao Ge, Yantao Shen +6
Conventional model upgrades for visual search systems require offline refresh of gallery features by feeding gallery images into new models (dubbed as "backfill"), which is time-co…