29 citations · 33 across the 7 of their papers we have counts for
7 papers
Physics-Grounded Motion Forecasting via Equation Discovery for Trajectory-Guided Image-to-Video Generation
Tao Feng, Xianbing Zhao, Zhenhua Chen +4
Recent advances in diffusion-based and autoregressive video generation models have achieved remarkable visual realism. However, these models typically lack accurate physical alignm…
A Tensor-based Convolutional Neural Network for Small Dataset Classification
Zhenhua Chen, David Crandall
Inspired by the ConvNets with structured hidden representations, we propose a Tensor-based Neural Network, TCNN. Different from ConvNets, TCNNs are composed of structured neurons r…
How to Accelerate Capsule Convolutions in Capsule Networks
Zhenhua Chen, Xiwen Li, Qian Lou +1
How to improve the efficiency of routing procedures in CapsNets has been studied a lot. However, the efficiency of capsule convolutions has largely been neglected. Capsule convolut…
Semantically Stealthy Adversarial Attacks against Segmentation Models
Zhenhua Chen, Chuhua Wang, David J. Crandall
Segmentation models have been found to be vulnerable to targeted and non-targeted adversarial attacks. However, the resulting segmentation outputs are often so damaged that it is e…
P-CapsNets: a General Form of Convolutional Neural Networks
Zhenhua Chen, Xiwen Li, Chuhua Wang +1
We propose Pure CapsNets (P-CapsNets) which is a generation of normal CNNs structurally. Specifically, we make three modifications to current CapsNets. First, we remove routing pro…
Generalized Capsule Networks with Trainable Routing Procedure
Zhenhua Chen, David Crandall
CapsNet (Capsule Network) was first proposed by~\citet{capsule} and later another version of CapsNet was proposed by~\citet{emrouting}. CapsNet has been proved effective in modelin…
Detecting Small, Densely Distributed Objects with Filter-Amplifier Networks and Loss Boosting
Zhenhua Chen, David Crandall, Robert Templeman
Detecting small, densely distributed objects is a significant challenge: small objects often contain less distinctive information compared to larger ones, and finer-grained precisi…