activity
20192022
most citedStructure-Feature based Graph Self-adaptive Pooling

65 citations · 152 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV20222 cited

Unsupervised Hierarchical Semantic Segmentation with Multiview Cosegmentation and Clustering Transformers

Tsung-Wei Ke, Jyh-Jing Hwang, Yunhui Guo +2

Unsupervised semantic segmentation aims to discover groupings within and across images that capture object and view-invariance of a category without external supervision. Grouping…

cs.RO20214 cited

Unsupervised Visual Attention and Invariance for Reinforcement Learning

Xudong Wang, Long Lian, Stella X. Yu

Vision-based reinforcement learning (RL) is successful, but how to generalize it to unknown test environments remains challenging. Existing methods focus on training an RL policy t…

cs.CV2020

Tied Block Convolution: Leaner and Better CNNs with Shared Thinner Filters

Xudong Wang, Stella X. Yu

Convolution is the main building block of convolutional neural networks (CNN). We observe that an optimized CNN often has highly correlated filters as the number of channels increa…

eess.IV202062 cited

Volumetric Attention for 3D Medical Image Segmentation and Detection

Xudong Wang, Shizhong Han, Yunqiang Chen +2

A volumetric attention(VA) module for 3D medical image segmentation and detection is proposed. VA attention is inspired by recent advances in video processing, enables 2.5D network…

cs.SI202065 cited

Structure-Feature based Graph Self-adaptive Pooling

Liang Zhang, Xudong Wang, Hongsheng Li +6

Various methods to deal with graph data have been proposed in recent years. However, most of these methods focus on graph feature aggregation rather than graph pooling. Besides, th…

cs.CV201919 cited

Towards Universal Object Detection by Domain Attention

Xudong Wang, Zhaowei Cai, Dashan Gao +1

Despite increasing efforts on universal representations for visual recognition, few have addressed object detection. In this paper, we develop an effective and efficient universal…