Yiyi Liao

Zhejiang University

I am a tenure-track research professor in Zhejiang University. Before that, I was a Postdoc in Autonomous Vision Group, a part of the University of Tübingen and the MPI for Intelligent Systems, working with Prof. Andreas Geiger. I received my Ph.D. in Control Science and Engineering from Zhejiang University in June 2018 and the B.S. degree from Xi’an Jiaotong University in 2013.

My research interest lies in 3D computer vision, including 3D scene understanding, 3D reconstruction, depth estimation and 3D controllable image synthesis.

For prospective students interested in computer vision, feel free to contact me via email!

news

Sep 29, 2021 Two papers (1 oral, 1 poster) are accepted to NeurIPS 2021.
Jun 24, 2021 Our work SMD-Nets was featured on the CVPR Daily and the BEST OF CVPR of Computer Vision News.
Jun 2, 2021 I will be joining Zhejiang University as a tenure-track assistant professor this September!
May 31, 2021 I will serve as an Area Chair for BMVC 2021.
May 20, 2021 I was acknowledged as Outstanding Reviewer at CVPR 2021.

selected publications

Full publication list can be found on Google Scholar.
*equal contribution; corresponding author.

2021

  1. Shape As Points: A Differentiable Poisson Solver
    In Advances in Neural Information Processing Systems (NeurIPS) 2021
  2. On the Frequency Bias of Generative Models
    On the Frequency Bias of Generative Models
    Schwarz, Katja, Liao, Yiyi, and Geiger, Andreas
    In Advances in Neural Information Processing Systems (NeurIPS) 2021
  3. KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
    KITTI-360: A Novel Dataset and Benchmarks for Urban Scene Understanding in 2D and 3D
    Liao, Yiyi, Xie, Jun, and Geiger, Andreas
    Arxiv 2021
  4. KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs
    KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs
    In Proc. of the IEEE International Conf. on Computer Vision (ICCV) 2021
  5. SMD-Nets: Stereo Mixture Density Networks
    SMD-Nets: Stereo Mixture Density Networks
    In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2021
  6. Learning Steering Kernels for Guided Depth Completion
    Learning Steering Kernels for Guided Depth Completion
    IEEE Trans. on Image Processing (TIP) 2021

2020

  1. GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
    GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
    In Advances in Neural Information Processing Systems (NeurIPS) 2020
  2. Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis
    Towards Unsupervised Learning of Generative Models for 3D Controllable Image Synthesis
    In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2020

2019

  1. Connecting the Dots: Learning Representations for Active Monocular Depth Estimation
    Connecting the Dots: Learning Representations for Active Monocular Depth Estimation
    In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2019

2018

  1. Deep Marching Cubes: Learning Explicit Surface Representations
    Deep Marching Cubes: Learning Explicit Surface Representations
    Liao, Yiyi, Donné, Simon, and Geiger, Andreas
    In Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) 2018
  2. On the Integration of Optical Flow and Action Recognition
    On the Integration of Optical Flow and Action Recognition
    In German Conference on Pattern Recognition (GCPR) 2018

2017

  1. Graph Regularized Auto-encoders for Image Representation
    Graph Regularized Auto-encoders for Image Representation
    Liao, Yiyi, Wang, Yue, and Liu, Yong
    IEEE Trans. on Image Processing (TIP) 2017
  2. Place Classification with a Graph Regularized Deep Neural Network
    Place Classification with a Graph Regularized Deep Neural Network
    IEEE Trans. on Cognitive and Developmental Systems (TCDS) 2017
  3. Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation
    Parse Geometry from a Line: Monocular Depth Estimation with Partial Laser Observation
    In Proc. of the IEEE International Conf. on Robotics and Automation (ICRA) 2017

2016

  1. Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks
    Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks
    In Proc. of the IEEE International Conf. on Robotics and Automation (ICRA) 2016