26 citations · 97 across the 14 of their papers we have counts for
12 papers · 1 filter
Spectral Graphormer: Spectral Graph-based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images
Tze Ho Elden Tse, Franziska Mueller, Zhengyang Shen +8
We propose a novel transformer-based framework that reconstructs two high fidelity hands from multi-view RGB images. Unlike existing hand pose estimation methods, where one typical…
HD-Fusion: Detailed Text-to-3D Generation Leveraging Multiple Noise Estimation
Jinbo Wu, Xiaobo Gao, Xing Liu +5
In this paper, we study Text-to-3D content generation leveraging 2D diffusion priors to enhance the quality and detail of the generated 3D models. Recent progress (Magic3D) in text…
PDO-s3DCNNs: Partial Differential Operator Based Steerable 3D CNNs
Zhengyang Shen, Tao Hong, Qi She +2
Steerable models can provide very general and flexible equivariance by formulating equivariance requirements in the language of representation theory and feature fields, which has…
End-to-End High Accuracy License Plate Recognition Based on Depthwise Separable Convolution Networks
Song-Ren Wang, Hong-Yang Shih, Zheng-Yi Shen +1
Automatic license plate recognition plays a crucial role in modern transportation systems such as for traffic monitoring and vehicle violation detection. In real-world scenarios, l…
Accurate Point Cloud Registration with Robust Optimal Transport
Zhengyang Shen, Jean Feydy, Peirong Liu +4
This work investigates the use of robust optimal transport (OT) for shape matching. Specifically, we show that recent OT solvers improve both optimization-based and deep learning m…
Inter-intra Variant Dual Representations forSelf-supervised Video Recognition
Lin Zhang, Qi She, Zhengyang Shen +1
Contrastive learning applied to self-supervised representation learning has seen a resurgence in deep models. In this paper, we find that existing contrastive learning based soluti…
PDO-eConvs: Partial Differential Operator Based Equivariant Convolutions
Zhengyang Shen, Lingshen He, Zhouchen Lin +1
Recent research has shown that incorporating equivariance into neural network architectures is very helpful, and there have been some works investigating the equivariance of networ…
Anatomical Data Augmentation via Fluid-based Image Registration
Zhengyang Shen, Zhenlin Xu, Sahin Olut +1
We introduce a fluid-based image augmentation method for medical image analysis. In contrast to existing methods, our framework generates anatomically meaningful images via interpo…
Region-specific Diffeomorphic Metric Mapping
Zhengyang Shen, François-Xavier Vialard, Marc Niethammer
We introduce a region-specific diffeomorphic metric mapping (RDMM) registration approach. RDMM is non-parametric, estimating spatio-temporal velocity fields which parameterize the…
Networks for Joint Affine and Non-parametric Image Registration
Zhengyang Shen, Xu Han, Zhenlin Xu +1
We introduce an end-to-end deep-learning framework for 3D medical image registration. In contrast to existing approaches, our framework combines two registration methods: an affine…
End-to-End Subtitle Detection and Recognition for Videos in East Asian Languages via CNN Ensemble with Near-Human-Level Performance
Yan Xu, Siyuan Shan, Ziming Qiu +5
In this paper, we propose an innovative end-to-end subtitle detection and recognition system for videos in East Asian languages. Our end-to-end system consists of multiple stages.…
Learning Multi-level Features For Sensor-based Human Action Recognition
Yan Xu, Zhengyang Shen, Xin Zhang +5
This paper proposes a multi-level feature learning framework for human action recognition using a single body-worn inertial sensor. The framework consists of three phases, respecti…