48 citations · 144 across the 28 of their papers we have counts for
6 papers · 1 filter
Learning Joint Latent Space EBM Prior Model for Multi-layer Generator
Jiali Cui, Ying Nian Wu, Tian Han
This paper studies the fundamental problem of learning multi-layer generator models. The multi-layer generator model builds multiple layers of latent variables as a prior model on…
Learning Sparse Latent Representations for Generator Model
Hanao Li, Tian Han
Sparsity is a desirable attribute. It can lead to more efficient and more effective representations compared to the dense model. Meanwhile, learning sparse latent representations h…
Learning from the Tangram to Solve Mini Visual Tasks
Yizhou Zhao, Liang Qiu, Pan Lu +3
Current pre-training methods in computer vision focus on natural images in the daily-life context. However, abstract diagrams such as icons and symbols are common and important in…
STAR: Sparse Transformer-based Action Recognition
Feng Shi, Chonghan Lee, Liang Qiu +6
The cognitive system for human action and behavior has evolved into a deep learning regime, and especially the advent of Graph Convolution Networks has transformed the field in rec…
Joint Training of Variational Auto-Encoder and Latent Energy-Based Model
Tian Han, Erik Nijkamp, Linqi Zhou +3
This paper proposes a joint training method to learn both the variational auto-encoder (VAE) and the latent energy-based model (EBM). The joint training of VAE and latent EBM are b…
Replicating Active Appearance Model by Generator Network
Tian Han, Jiawen Wu, Ying Nian Wu
A recent Cell paper [Chang and Tsao, 2017] reports an interesting discovery. For the face stimuli generated by a pre-trained active appearance model (AAM), the responses of neurons…