27 citations · 57 across the 8 of their papers we have counts for
8 papers
Hierarchical Spherical CNNs with Lifting-based Adaptive Wavelets for Pooling and Unpooling
Mingxing Xu, Chenglin Li, Wenrui Dai +4
Pooling and unpooling are two essential operations in constructing hierarchical spherical convolutional neural networks (HS-CNNs) for comprehensive feature learning in the spherica…
Hybrid ISTA: Unfolding ISTA With Convergence Guarantees Using Free-Form Deep Neural Networks
Ziyang Zheng, Wenrui Dai, Duoduo Xue +3
It is promising to solve linear inverse problems by unfolding iterative algorithms (e.g., iterative shrinkage thresholding algorithm (ISTA)) as deep neural networks (DNNs) with lea…
LiftPool: Lifting-based Graph Pooling for Hierarchical Graph Representation Learning
Mingxing Xu, Wenrui Dai, Chenglin Li +2
Graph pooling has been increasingly considered for graph neural networks (GNNs) to facilitate hierarchical graph representation learning. Existing graph pooling methods commonly co…
Message Passing in Graph Convolution Networks via Adaptive Filter Banks
Xing Gao, Wenrui Dai, Chenglin Li +3
Graph convolution networks, like message passing graph convolution networks (MPGCNs), have been a powerful tool in representation learning of networked data. However, when data is…
Multi-dataset Pretraining: A Unified Model for Semantic Segmentation
Bowen Shi, Xiaopeng Zhang, Haohang Xu +4
Collecting annotated data for semantic segmentation is time-consuming and hard to scale up. In this paper, we for the first time propose a unified framework, termed as Multi-Datase…
Key-Point Sequence Lossless Compression for Intelligent Video Analysis
Weiyao Lin, Xiaoyi He, Wenrui Dai +4
Feature coding has been recently considered to facilitate intelligent video analysis for urban computing. Instead of raw videos, extracted features in the front-end are encoded and…