activity
20202023
most citedA Two-Stream Meticulous Processing Network for Retinal Vessel Segmentation

4 citations · 9 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CV2023

Revisiting Stereo Triangulation in UAV Distance Estimation

Jiafan Zhuang, Duan Yuan, Rihong Yan +3

Distance estimation plays an important role for path planning and collision avoidance of swarm UAVs. However, the lack of annotated data seriously hinders the related studies. In t…

cs.CV2023★ 2 cited

Advancing Volumetric Medical Image Segmentation via Global-Local Masked Autoencoder

Jia-Xin Zhuang, Luyang Luo, Hao Chen

Masked autoencoder (MAE) is a promising self-supervised pre-training technique that can improve the representation learning of a neural network without human intervention. However,…

cs.CV2023★ 2 cited

Video Semantic Segmentation with Inter-Frame Feature Fusion and Inner-Frame Feature Refinement

Jiafan Zhuang, Zilei Wang, Junjie Li

Video semantic segmentation aims to generate accurate semantic maps for each video frame. To this end, many works dedicate to integrate diverse information from consecutive frames…

eess.IV2022

OpenMedIA: Open-Source Medical Image Analysis Toolbox and Benchmark under Heterogeneous AI Computing Platforms

Jia-Xin Zhuang, Xiansong Huang, Yang Yang +6

In this paper, we present OpenMedIA, an open-source toolbox library containing a rich set of deep learning methods for medical image analysis under heterogeneous Artificial Intelli…

cs.CV2021

5th Place Solution for VSPW 2021 Challenge

Jiafan Zhuang, Yixin Zhang, Xinyu Hu +2

In this article, we introduce the solution we used in the VSPW 2021 Challenge. Our experiments are based on two baseline models, Swin Transformer and MaskFormer. To further boost p…

cs.CV2021★ 1 cited

Understanding of Kernels in CNN Models by Suppressing Irrelevant Visual Features in Images

Jia-Xin Zhuang, Wanying Tao, Jianfei Xing +3

Deep learning models have shown their superior performance in various vision tasks. However, the lack of precisely interpreting kernels in convolutional neural networks (CNNs) is b…