Xia Li

About Me

I am to be a tenure-track associate professor at School of Biomedical Engineering, Shanghai Jiao Tong University from spring of 2026. Now, I am a postdoctoral researcher at Institute for Biomedical Engineering, ETH Zurich, Switzerland, working with Prof. Marco Stampanoni. I obtained my Ph.D. degree from Department of Computer Science, ETH Zurich, Switzerland, in Dec. 2024, under the supervision of Prof. Joachim M. Buhmann, Prof. Antony J. Lomax and Dr. Ye Zhang. Before that I received my master’s degree from the Peking University, China, in Jul. 2017, advised by Prof. Hong Liu and Prof. Zhouchen Lin. Besdies, I got bachelor’s degree from School of Computer Science, Beijing University of Posts and Communications, China, in Jul. 2016. I was an intern at Bytedance and Google. I am an Area Chair of ICML, as well as reviewer for top-tier journals and conferences in the domain of machine learning, computer vision and medical physics.

SOGNet: Scene Overlap Graph Network for Panoptic Segmentation
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation

We leverage each object’s category, geometry and appearance features to perform relational embedding, and output a relation matrix that encodes overlap relations. In order to overcome the lack of supervision, we introduce a differentiable module to resolve the overlap between any pair of instances.

Feb 7, 2020
Dynamic System Inspired Adaptive Time Stepping Controller for Residual Networks Families
Dynamic System Inspired Adaptive Time Stepping Controller for Residual Networks Families

We analyze the effects of time stepping on the Euler method and ResNets. We establish a stability condition for ResNets with step sizes and weight parameters, and point out the effects of step sizes on the stability and performance. Inspired by our analyses, we develop an adaptive time stepping controller that is dependent on the parameters of the current step, and aware of previous steps.

Feb 7, 2020
ICCV 2019 Oral
ICCV 2019 Oral

Oral presentation for EMANet

Nov 1, 2019
Self-Refining Deep Symmetry Enhanced Network for Rain Removal
Self-Refining Deep Symmetry Enhanced Network for Rain Removal

A Self-Refining Deep Symmetry Enhanced Network (DSEN) for rain removal that extracts rotation equivariant features and uses a self-refining mechanism to remove accumulated rain streaks in a coarse-to-fine manner.

Sep 22, 2019
Expectation Maximization Attention Networks for Semantic Segmentation
Expectation Maximization Attention Networks for Semantic Segmentation

We formulate the attention mechanism into an expectation-maximization manner and iteratively estimate a much more compact set of bases upon which the attention maps are computed.

Jul 22, 2019
R^2 Net Recurrent and Recursive Network for Sparse View CT Artifacts Removal
R^2 Net Recurrent and Recursive Network for Sparse View CT Artifacts Removal

We propose a novel neural network architecture to reduce streak artifacts generated in sparse-view 2D Cone Beam Computed To-mography (CBCT) image reconstruction.

Jun 19, 2019
Multi-label classification of PCB defects based on convolutional neural network
Multi-label classification of PCB defects based on convolutional neural network

A multi-label classification method based on Convolutional Neural Network for PCB defect detection that can simultaneously identify multiple defect types, improving detection accuracy and efficiency.

Oct 22, 2018
Recurrent Squeeze-and-Excitation Net for Single Image Deraining
Recurrent Squeeze-and-Excitation Net for Single Image Deraining

We propose a novel deep network architecture based on deep convolutional and recurrent neural networksfor single image deraining.

Jul 19, 2018