Xulab Publishes Two Papers in Top Computer Vision Conference
Two papers from Dr. Min Xu’s lab were accepted by the International Conference of Computer Vision (ICCV), a top conference in computer vision. These papers developed unsupervised and weakly supervised methods for automating the analysis of in situ cryo-electron tomography data, which will facilitate the detection and recovery of macromolecular structures.
The papers were titled:
- End-to-end robust joint unsupervised image alignment and clustering
- Weakly supervised 3D semantic segmentation using cross-image consensus and inter-voxel affinity relations
One of the first authors, Taylor Zeng, is a fifth-year Ph.D. student in the Carnegie Mellon-University of Pittsburgh Ph.D. Program in Computational Biology (CPCB). His paper is a follow-up of his previous first-author paper in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).