2 citations · 2 across the 4 of their papers we have counts for
4 papers
Bayesian Evidential Learning for Few-Shot Classification
Xiongkun Linghu, Yan Bai, Yihang Lou +4
Few-Shot Classification(FSC) aims to generalize from base classes to novel classes given very limited labeled samples, which is an important step on the path toward human-like mach…
Switchable Representation Learning Framework with Self-compatibility
Shengsen Wu, Yan Bai, Yihang Lou +3
Real-world visual search systems involve deployments on multiple platforms with different computing and storage resources. Deploying a unified model that suits the minimal-constrai…
Dual-Tuning: Joint Prototype Transfer and Structure Regularization for Compatible Feature Learning
Yan Bai, Jile Jiao, Shengsen Wu +4
Visual retrieval system faces frequent model update and deployment. It is a heavy workload to re-extract features of the whole database every time.Feature compatibility enables the…
Neighborhood Consensus Contrastive Learning for Backward-Compatible Representation
Shengsen Wu, Liang Chen, Yihang Lou +4
In object re-identification (ReID), the development of deep learning techniques often involves model updates and deployment. It is unbearable to re-embedding and re-index with the…