activity
20192023
most citedOn the Number of Linear Regions of Convolutional Neural Networks

25 citations · 77 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2023★ 1 cited

A Unified Query-based Paradigm for Camouflaged Instance Segmentation

Bo Dong, Jialun Pei, Rongrong Gao +3

Due to the high similarity between camouflaged instances and the background, the recently proposed camouflaged instance segmentation (CIS) faces challenges in accurate localization…

eess.IV2023★ 10 cited

Rethinking Polyp Segmentation from an Out-of-Distribution Perspective

Ge-Peng Ji, Jing Zhang, Dylan Campbell +2

Unlike existing fully-supervised approaches, we rethink colorectal polyp segmentation from an out-of-distribution perspective with a simple but effective self-supervised learning a…

cs.CV2023★ 9 cited

Feature Shrinkage Pyramid for Camouflaged Object Detection with Transformers

Zhou Huang, Hang Dai, Tian-Zhu Xiang +4

Vision transformers have recently shown strong global context modeling capabilities in camouflaged object detection. However, they suffer from two major limitations: less effective…

cs.CV2023★ 1 cited

Memory-aided Contrastive Consensus Learning for Co-salient Object Detection

Peng Zheng, Jie Qin, Shuo Wang +2

Co-Salient Object Detection (CoSOD) aims at detecting common salient objects within a group of relevant source images. Most of the latest works employ the attention mechanism for f…

cs.LG2022

Balanced Self-Paced Learning for AUC Maximization

Bin Gu, Chenkang Zhang, Huan Xiong +1

Learning to improve AUC performance is an important topic in machine learning. However, AUC maximization algorithms may decrease generalization performance due to the noisy data. S…

cs.LG2022

Lower and Upper Bounds for Numbers of Linear Regions of Graph Convolutional Networks

Hao Chen, Yu Guang Wang, Huan Xiong

The research for characterizing GNN expressiveness attracts much attention as graph neural networks achieve a champion in the last five years. The number of linear regions has been…

cs.CV2022

Dynamic Prototype Convolution Network for Few-Shot Semantic Segmentation

Jie Liu, Yanqi Bao, Guo-Sen Xie +3

The key challenge for few-shot semantic segmentation (FSS) is how to tailor a desirable interaction among support and query features and/or their prototypes, under the episodic tra…

cs.CV2022★ 1 cited

Implicit Motion Handling for Video Camouflaged Object Detection

Xuelian Cheng, Huan Xiong, Deng-Ping Fan +4

We propose a new video camouflaged object detection (VCOD) framework that can exploit both short-term dynamics and long-term temporal consistency to detect camouflaged objects from…

cs.LG2020★ 18 cited

Learning to Learn Variational Semantic Memory

Xiantong Zhen, Yingjun Du, Huan Xiong +3

In this paper, we introduce variational semantic memory into meta-learning to acquire long-term knowledge for few-shot learning. The variational semantic memory accrues and stores…

cs.CV2020★ 11 cited

Learning to Learn with Variational Information Bottleneck for Domain Generalization

Yingjun Du, Jun Xu, Huan Xiong +4

Domain generalization models learn to generalize to previously unseen domains, but suffer from prediction uncertainty and domain shift. In this paper, we address both problems. We…

cs.LG2020★ 25 cited

On the Number of Linear Regions of Convolutional Neural Networks

H. Xiong, L. Huang, M. Yu +3

One fundamental problem in deep learning is understanding the outstanding performance of deep Neural Networks (NNs) in practice. One explanation for the superiority of NNs is that…

math.OC2019★ 1 cited

Fast Large-Scale Discrete Optimization Based on Principal Coordinate Descent

Huan Xiong, Mengyang Yu, Li Liu +3

Binary optimization, a representative subclass of discrete optimization, plays an important role in mathematical optimization and has various applications in computer vision and ma…