27 citations · 64 across the 8 of their papers we have counts for
11 papers · 1 filter
Collaborative Uncertainty in Multi-Agent Trajectory Forecasting
Bohan Tang, Yiqi Zhong, Ulrich Neumann +3
Uncertainty modeling is critical in trajectory forecasting systems for both interpretation and safety reasons. To better predict the future trajectories of multiple agents, recent…
Accurate 3D Facial Geometry Prediction by Multi-Task, Multi-Modal, and Multi-Representation Landmark Refinement Network
Cho-Ying Wu, Qiangeng Xu, Ulrich Neumann
This work focuses on complete 3D facial geometry prediction, including 3D facial alignment via 3D face modeling and face orientation estimation using the proposed multi-task, multi…
Grid-GCN for Fast and Scalable Point Cloud Learning
Qiangeng Xu, Xudong Sun, Cho-Ying Wu +2
Due to the sparsity and irregularity of the point cloud data, methods that directly consume points have become popular. Among all point-based models, graph convolutional networks (…
Deep RGB-D Canonical Correlation Analysis For Sparse Depth Completion
Yiqi Zhong, Cho-Ying Wu, Suya You +1
In this paper, we propose our Correlation For Completion Network (CFCNet), an end-to-end deep learning model that uses the correlation between two data sources to perform sparse de…
3DN: 3D Deformation Network
Weiyue Wang, Duygu Ceylan, Radomir Mech +1
Applications in virtual and augmented reality create a demand for rapid creation and easy access to large sets of 3D models. An effective way to address this demand is to edit or d…
Efficient Multi-Domain Dictionary Learning with GANs
Cho Ying Wu, Ulrich Neumann
In this paper, we propose the multi-domain dictionary learning (MDDL) to make dictionary learning-based classification more robust to data representing in different domains. We use…