Research
DeepHuman: 3D Human Reconstruction from a Single Image
Z. Zheng, T. Yu, Y. Wei, Q. Dai, Y. Liu
IEEE International Conference on Computer Vision 2019 -- ICCV 2019 Oral
We propose DeepHuman, a deep learning based framework for 3D human reconstruction from a single RGB image. We also contribute THuman, a 3D real-world human model dataset containing approximately 7000 models.
SimulCap : Single-View Human Performance Capture with Cloth Simulation
T. Yu, Z. Zheng, Y. Zhong, J. Zhao, Q. Dai, G. Pons-Moll, Y. Liu
IEEE Conference on Computer Vision and Pattern Recognition 2019 -- CVPR 2019
This paper proposes a new method for live free-viewpoint human performance capture with dynamic details (e.g., cloth wrinkles) using a single RGBD camera. By incorporating cloth simulation into the performance capture pipeline, we can generate plausible cloth dynamics and cloth-body interactions.
HybridFusion: Real-time Performance Capture Using a Single Depth Sensor and Sparse IMUs
Z. Zheng, T. Yu, H. Li, K. Guo, Q. Dai, L. Fang, Y. Liu
European Conference on Computer Vision 2018 -- ECCV 2018
We propose a light-weight and highly robust real-time human performance capture method based on a single depth camera and sparse inertial measurement units (IMUs).
DoubleFusion: Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor
T. Yu, Z. Zheng, K. Guo, J. Zhao, Q. Dai, H. Li, G. Pons-Moll, Y. Liu
IEEE Conference on Computer Vision and Pattern Recognition 2018 -- CVPR 2018 Oral
We propose DoubleFusion, a new real-time system to simultaneously reconstruct detailed geometry, non-rigid motion and the inner human body shape from a single depth camera.