Self-supervised Spatial Reasoning on Multi-View Line Drawings

1 code implementation • CVPR 2022 • Siyuan Xiang, Anbang Yang, Yanfei Xue, Yaoqing Yang, Chen Feng

Based on the fact that self-supervised learning is helpful when a large number of data are available, we propose two self-supervised learning approaches to improve the baseline performance for view consistency reasoning and camera pose reasoning tasks on the SPARE3D dataset.

Binary Classification Contrastive Learning +2

SPARE3D: A Dataset for SPAtial REasoning on Three-View Line Drawings

1 code implementation • CVPR 2020 • Wenyu Han, Siyuan Xiang, Chenhui Liu, Ruoyu Wang, Chen Feng

Our experiments show that although convolutional networks have achieved superhuman performance in many visual learning tasks, their spatial reasoning performance on SPARE3D tasks is either lower than average human performance or even close to random guesses.

Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks

no code implementations • 20 Apr 2017 • Cem M. Deniz, Siyuan Xiang, Spencer Hallyburton, Arakua Welbeck, James S. Babb, Stephen Honig, Kyunghyun Cho, Gregory Chang

However, manual segmentation of MR images of bone is time-consuming, limiting the use of MRI measurements in the clinical practice.

Management Segmentation