18 citations · 29 across the 6 of their papers we have counts for
7 papers
Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation
Mengyao Zhai, Lei Chen, Jiawei He +3
Humans accumulate knowledge in a lifelong fashion. Modern deep neural networks, on the other hand, are susceptible to catastrophic forgetting: when adapted to perform new tasks, th…
Adaptive Appearance Rendering
Mengyao Zhai, Ruizhi Deng, Jiacheng Chen +3
We propose an approach to generate images of people given a desired appearance and pose. Disentangled representations of pose and appearance are necessary to handle the compound va…
Improving Sequential Latent Variable Models with Autoregressive Flows
Joseph Marino, Lei Chen, Jiawei He +1
We propose an approach for improving sequence modeling based on autoregressive normalizing flows. Each autoregressive transform, acting across time, serves as a moving frame of ref…
Adapting Grad-CAM for Embedding Networks
Lei Chen, Jianhui Chen, Hossein Hajimirsadeghi +1
The gradient-weighted class activation mapping (Grad-CAM) method can faithfully highlight important regions in images for deep model prediction in image classification, image capti…
Lifelong GAN: Continual Learning for Conditional Image Generation
Mengyao Zhai, Lei Chen, Fred Tung +3
Lifelong learning is challenging for deep neural networks due to their susceptibility to catastrophic forgetting. Catastrophic forgetting occurs when a trained network is not able…
Learning to Forecast Videos of Human Activity with Multi-granularity Models and Adaptive Rendering
Mengyao Zhai, Jiacheng Chen, Ruizhi Deng +3
We propose an approach for forecasting video of complex human activity involving multiple people. Direct pixel-level prediction is too simple to handle the appearance variability i…