Computer Vision News 4 be easily shared among people.” To his knowledge, this is the first work to address the problem of aligning pairs of 3D scene graphs. Its approach sets SGAligner apart – rather than relying on metric data, it operates exclusively on the graph level. This unique perspective confers robustness against various challenges, including noise, in-thewild scenarios, and overlap. The implications of this approach are far-reaching, opening doors to applications in mixed and augmented reality and even SLAM. Sayan started his master’s degree last September and took up this project in the first semester. One key personal hurdle was the balancing act of pursuing all this while moving to Zurich and adapting to new surroundings. However, any obstacles were surmountable with the support of dedicated supervisors like Ondrej Miksik, Marc Pollefeys, Dániel Baráth, andIroArmeni. “I originally had reached out to Iro for the project when I was moving to ETH to start my master’s,” he recalls. “She has been very helpful in understanding where I need support and where I can be independent. Daniel is very experienced with point cloud registration and all the technical parts. He was the best person in the community to help me figure out the downstream applications. Marc is one of the grandfathers of 3D computer vision. ICCV Accepted Paper
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