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CVPR 2022: Two papers accepted

We are happy to announce that the Augmented Vision group will present two papers in the upcoming CVPR 2022 Conference from June 19th-23rd in New Orleans, USA. The IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) is the premier annual computer vision event internationally. Homepage: https://cvpr2022.thecvf.com/

The two accepted papers are:

Summary: ZebraPose sets a new paradigm on model-based 6DoF object pose estimation by using a binary object surface encoding to train a neural network to predict the locations of model vertices in a coarse to fine manner. ZebraPose shows a major improvement over the state-of-the-art on several datasets of the BOP Object Pose Estimation benchmark.

Preprinthttps://av.dfki.de/publications/zebrapose-coarse-to-fine-surface-encoding-for-6dof-object-pose-estimation/

Contact: Yongzhi Su, Dr. Jason Rambach

Summary: We propose a novel Multi-Sphere Image representation called Soft Occlusion MSI (SOMSI) and efficient rendering technique that produces accurate spherical novel-views from a sparse spherical light-field. SOMSI models appearance features in a smaller set (e.g. 3) of occlusion levels instead of larger number (e.g. 64) of MSI spheres. Experiments on both synthetic and real-world spherical light-fields demonstrate that using SOMSI can provide a good balance between accuracy and run-time. SOMSI view synthesis quality is on-par with state-of-the-art models like NeRF, while being 2 orders of magnitude faster.

For more information, please visit the project page at https://tedyhabtegebrial.github.io/somsi

Contact: Tewodros A Habtegebrial