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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 arXiv |
15.06.2021