1 citations · 1 across the 2 of their papers we have counts for
4 papers
Few-Shot Classification with Feature Map Reconstruction Networks
Davis Wertheimer, Luming Tang, Bharath Hariharan
In this paper we reformulate few-shot classification as a reconstruction problem in latent space. The ability of the network to reconstruct a query feature map from support feature…
Revisiting Pose-Normalization for Fine-Grained Few-Shot Recognition
Luming Tang, Davis Wertheimer, Bharath Hariharan
Few-shot, fine-grained classification requires a model to learn subtle, fine-grained distinctions between different classes (e.g., birds) based on a few images alone. This requires…
Multi-Entity Dependence Learning with Rich Context via Conditional Variational Auto-encoder
Luming Tang, Yexiang Xue, Di Chen +1
Multi-Entity Dependence Learning (MEDL) explores conditional correlations among multiple entities. The availability of rich contextual information requires a nimble learning scheme…
Hierarchical Deep Recurrent Architecture for Video Understanding
Luming Tang, Boyang Deng, Haiyu Zhao +1
This paper introduces the system we developed for the Youtube-8M Video Understanding Challenge, in which a large-scale benchmark dataset was used for multi-label video classificati…