Search Results for author: Cheng Jiang

Found 11 papers, 5 papers with code

MixFormer: End-to-End Tracking with Iterative Mixed Attention

1 code implementation6 Feb 2023 Yutao Cui, Cheng Jiang, Gangshan Wu, LiMin Wang

Our core design is to utilize the flexibility of attention operations, and propose a Mixed Attention Module (MAM) for simultaneous feature extraction and target information integration.

Visual Object Tracking

3D Shuffle-Mixer: An Efficient Context-Aware Vision Learner of Transformer-MLP Paradigm for Dense Prediction in Medical Volume

no code implementations14 Apr 2022 Jianye Pang, Cheng Jiang, Yihao Chen, Jianbo Chang, Ming Feng, Renzhi Wang, Jianhua Yao

Therefore, designing an elegant and efficient vision transformer learner for dense prediction in medical volume is promising and challenging.

Inductive Bias

MixFormer: End-to-End Tracking with Iterative Mixed Attention

1 code implementation CVPR 2022 Yutao Cui, Cheng Jiang, LiMin Wang, Gangshan Wu

Our core design is to utilize the flexibility of attention operations, and propose a Mixed Attention Module (MAM) for simultaneous feature extraction and target information integration.

Semi-Supervised Video Object Segmentation Visual Object Tracking

Target Transformed Regression for Accurate Tracking

1 code implementation1 Apr 2021 Yutao Cui, Cheng Jiang, LiMin Wang, Gangshan Wu

Accurate tracking is still a challenging task due to appearance variations, pose and view changes, and geometric deformations of target in videos.

regression Visual Object Tracking +1

Blind deblurring for microscopic pathology images using deep learning networks

no code implementations24 Nov 2020 Cheng Jiang, Jun Liao, Pei Dong, Zhaoxuan Ma, De Cai, Guoan Zheng, Yueping Liu, Hong Bu, Jianhua Yao

Artificial Intelligence (AI)-powered pathology is a revolutionary step in the world of digital pathology and shows great promise to increase both diagnosis accuracy and efficiency.

Deblurring

Fully Convolutional Online Tracking

2 code implementations15 Apr 2020 Yutao Cui, Cheng Jiang, Li-Min Wang, Gangshan Wu

To tackle this issue, we present the fully convolutional online tracking framework, coined as FCOT, and focus on enabling online learning for both classification and regression branches by using a target filter based tracking paradigm.

Real-Time Visual Tracking regression

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