3 citations · 9 across the 5 of their papers we have counts for
6 papers
Continuous Latent Process Flows
Ruizhi Deng, Marcus A. Brubaker, Greg Mori +1
Partial observations of continuous time-series dynamics at arbitrary time stamps exist in many disciplines. Fitting this type of data using statistical models with continuous dynam…
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…
Variational Hyper RNN for Sequence Modeling
Ruizhi Deng, Yanshuai Cao, Bo Chang +3
In this work, we propose a novel probabilistic sequence model that excels at capturing high variability in time series data, both across sequences and within an individual sequence…
Point Process Flows
Nazanin Mehrasa, Ruizhi Deng, Mohamed Osama Ahmed +5
Event sequences can be modeled by temporal point processes (TPPs) to capture their asynchronous and probabilistic nature. We propose an intensity-free framework that directly model…
Characterizing Adversarial Examples Based on Spatial Consistency Information for Semantic Segmentation
Chaowei Xiao, Ruizhi Deng, Bo Li +3
Deep Neural Networks (DNNs) have been widely applied in various recognition tasks. However, recently DNNs have been shown to be vulnerable against adversarial examples, which can m…
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…