Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Zi Wang

Zi Wang
Alert button

TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving


Mar 17, 2023
Shaoheng Fang, Zi Wang, Yiqi Zhong, Junhao Ge, Siheng Chen, Yanfeng Wang

Add code
Alert button

Figure 1 for TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving
Figure 2 for TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving
Figure 3 for TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving
Figure 4 for TBP-Former: Learning Temporal Bird's-Eye-View Pyramid for Joint Perception and Prediction in Vision-Centric Autonomous Driving
* CVPR 2023 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Oriented Object Detection in Optical Remote Sensing Images: A Survey


Feb 21, 2023
Kun Wang, Zhang Li, Ang Su, Zi Wang

Add code
Alert button

Figure 1 for Oriented Object Detection in Optical Remote Sensing Images: A Survey
Figure 2 for Oriented Object Detection in Optical Remote Sensing Images: A Survey
Figure 3 for Oriented Object Detection in Optical Remote Sensing Images: A Survey
Figure 4 for Oriented Object Detection in Optical Remote Sensing Images: A Survey

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Bridging the Domain Gap in Satellite Pose Estimation: a Self-Training Approach based on Geometrical Constraints


Dec 23, 2022
Zi Wang, Minglin Chen, Yulan Guo, Zhang Li, Qifeng Yu

Add code
Alert button

Figure 1 for Bridging the Domain Gap in Satellite Pose Estimation: a Self-Training Approach based on Geometrical Constraints
Figure 2 for Bridging the Domain Gap in Satellite Pose Estimation: a Self-Training Approach based on Geometrical Constraints
Figure 3 for Bridging the Domain Gap in Satellite Pose Estimation: a Self-Training Approach based on Geometrical Constraints
Figure 4 for Bridging the Domain Gap in Satellite Pose Estimation: a Self-Training Approach based on Geometrical Constraints
* 11 pages, 5 figures. Submitted to IEEE TAES, major revision 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes


Dec 20, 2022
Zhou Fan, Xinran Han, Zi Wang

Add code
Alert button

Figure 1 for HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes
Figure 2 for HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes
Figure 3 for HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes
Figure 4 for HyperBO+: Pre-training a universal prior for Bayesian optimization with hierarchical Gaussian processes

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

CloudBrain-ReconAI: An Online Platform for MRI Reconstruction and Image Quality Evaluation


Dec 04, 2022
Yirong Zhou, Chen Qian, Jiayu Li, Zi Wang, Yu Hu, Biao Qu, Liuhong Zhu, Jianjun Zhou, Taishan Kang, Jianzhong Lin, Qing Hong, Jiyang Dong, Di Guo, Xiaobo Qu

Add code
Alert button

Figure 1 for CloudBrain-ReconAI: An Online Platform for MRI Reconstruction and Image Quality Evaluation
Figure 2 for CloudBrain-ReconAI: An Online Platform for MRI Reconstruction and Image Quality Evaluation
Figure 3 for CloudBrain-ReconAI: An Online Platform for MRI Reconstruction and Image Quality Evaluation
Figure 4 for CloudBrain-ReconAI: An Online Platform for MRI Reconstruction and Image Quality Evaluation
* 8 pages, 11 figures 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Alternating Deep Low Rank Approach for Exponential Function Reconstruction and Its Biomedical Magnetic Resonance Applications


Nov 24, 2022
Yihui Huang, Zi Wang, Xinlin Zhang, Jian Cao, Zhangren Tu, Di Guo, Xiaobo Qu

Add code
Alert button

Figure 1 for Alternating Deep Low Rank Approach for Exponential Function Reconstruction and Its Biomedical Magnetic Resonance Applications
Figure 2 for Alternating Deep Low Rank Approach for Exponential Function Reconstruction and Its Biomedical Magnetic Resonance Applications
Figure 3 for Alternating Deep Low Rank Approach for Exponential Function Reconstruction and Its Biomedical Magnetic Resonance Applications
Figure 4 for Alternating Deep Low Rank Approach for Exponential Function Reconstruction and Its Biomedical Magnetic Resonance Applications
* 14 pages 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging


Oct 23, 2022
Zi Wang, Haoming Fang, Chen Qian, Boxuan Shi, Lijun Bao, Liuhong Zhu, Jianjun Zhou, Wenping Wei, Jianzhong Lin, Di Guo, Xiaobo Qu

Add code
Alert button

Figure 1 for A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging
Figure 2 for A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging
Figure 3 for A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging
Figure 4 for A Faithful Deep Sensitivity Estimation for Accelerated Magnetic Resonance Imaging
* 10 pages, 8 figures, 3 tables 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Physics-informed deep diffusion MRI reconstruction: break the bottleneck of training data in artificial intelligence


Oct 20, 2022
Chen Qian, Zi Wang, Xinlin Zhang, Qingrui Cai, Taishan Kang, Boyu Jiang, Ran Tao, Zhigang Wu, Di Guo, Xiaobo Qu

Add code
Alert button

Figure 1 for Physics-informed deep diffusion MRI reconstruction: break the bottleneck of training data in artificial intelligence
Figure 2 for Physics-informed deep diffusion MRI reconstruction: break the bottleneck of training data in artificial intelligence
Figure 3 for Physics-informed deep diffusion MRI reconstruction: break the bottleneck of training data in artificial intelligence
* 5 pages, 5 figures 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Plex: Towards Reliability using Pretrained Large Model Extensions


Jul 15, 2022
Dustin Tran, Jeremiah Liu, Michael W. Dusenberry, Du Phan, Mark Collier, Jie Ren, Kehang Han, Zi Wang, Zelda Mariet, Huiyi Hu, Neil Band, Tim G. J. Rudner, Karan Singhal, Zachary Nado, Joost van Amersfoort, Andreas Kirsch, Rodolphe Jenatton, Nithum Thain, Honglin Yuan, Kelly Buchanan, Kevin Murphy, D. Sculley, Yarin Gal, Zoubin Ghahramani, Jasper Snoek, Balaji Lakshminarayanan

Add code
Alert button

Figure 1 for Plex: Towards Reliability using Pretrained Large Model Extensions
Figure 2 for Plex: Towards Reliability using Pretrained Large Model Extensions
Figure 3 for Plex: Towards Reliability using Pretrained Large Model Extensions
Figure 4 for Plex: Towards Reliability using Pretrained Large Model Extensions
* Code available at https://goo.gle/plex-code 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Pre-training helps Bayesian optimization too


Jul 07, 2022
Zi Wang, George E. Dahl, Kevin Swersky, Chansoo Lee, Zelda Mariet, Zachary Nado, Justin Gilmer, Jasper Snoek, Zoubin Ghahramani

Add code
Alert button

Figure 1 for Pre-training helps Bayesian optimization too
Figure 2 for Pre-training helps Bayesian optimization too
Figure 3 for Pre-training helps Bayesian optimization too
Figure 4 for Pre-training helps Bayesian optimization too
* ICML2022 Workshop on Adaptive Experimental Design and Active Learning in the Real World. arXiv admin note: substantial text overlap with arXiv:2109.08215 
   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email
1
2
3
4
5
>>