IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021), June 19–25, 2021. Virtual

       We are happy to announce that MCML researchers are represented with the following paper(s) at CVPR 2021.

       4D panoptic segmentation
M. Aygun, A. Osep, M. Weber, M. Maximov, C. Stachniss, J. Behley and L. Leal-Taixe

       Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction
A. Božič, P. Palafox, M. Zollhöfer, J. Thies, A. Dai and M. Nießner

       Scan2Cap: Context-aware Dense Captioning in RGB-D Scans
D. Z. Chen, A. Gholami, M. Nießner and A. X. Chang

       SPSG: Self-Supervised Photometric Scene Generation from RGB-D Scans
A. Dai, Y. Siddiqui, J. Thies, J. Valentin and M. Nießner

       NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go
M. Eisenberger, D. Novotny, G. Kerchenbaum, P. Labatut, N. Neverova, D. Cremers and A. Vedaldi

       Dynamic Neural Radiance Fields for Monocular 4D Facial Avatar Reconstruction
G. Gafni, J. Thies, M. Zollhöfer and M. Nießner

       Isometric Multi-Shape Matching
M. Gao, Z. Lähner, J. Thunberg, D. Cremers and F. Bernard

       Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts
J. Hou, B. Graham, M. Nießner and S. Xie

       Neural Response Interpretation through the Lens of Critical Pathways
A. Khakzar, S. Baselizadeh, S. Khanduja, C. Rupprecht, S. T. Kim and N. Navab

       Seeing Behind Objects for 3D Multi-Object Tracking in RGB-D Sequences
N. Müller, Y.-S. Wong, N. J. Mitra, A. Dai and M. Nießner

       RfD-Net: Point Scene Understanding by Semantic Instance Reconstruction
Y. Nie, J. Hou, X. Han and M. Nießner

       Post-hoc Uncertainty Calibration for Domain Drift Scenarios
C. Tomani, S. Gruber, M. E. Erdem, D. Cremers and F. Buettner