27 DAILY ICCV Friday SGAligner He’s been very helpful in driving the project. Ondrej always had a highlevel understanding of the project, which helped me because, as a first author, it’s easy to get lost in the technicalities when you work on a project. The last year of working with them helped me get my internship at Qualcomm, and I’m very grateful for all their help and advice.” The impact of SGAligner is already being felt across the computer vision community. Making the code public and releasing the paper on arXiv has sparked interest among fellow researchers exploring various avenues for further development. Potential directions include crossmodal alignments, such as aligning point clouds with CAD models or other modalities, applications in scene retrieval from extensive databases, and multiple downstream applications in AR scenarios. The benefit of SGAligner’s lightweight and privacy-aware scene graphs to the community cannot be overstated. As lead author, this is the first time Sayan has had a paper accepted at a top conference – a fantastic achievement. Does he have any wisdom for those whose papers were not accepted this year? “The computer vision community has grown manifold in the last few years,” he responds. “Please do not be disheartened that your paper wasn’t accepted because we have all been there at some point. Always have a high-level understanding of where your work could play into both industry and academia. It’s not only about solving a new problem but also having real-life applications of the problem. SGAligner was a new problem, but we could also find multiple real-life applications where we could make a difference. Also, don’t forget to do ablations and understand which other works might be relevant for comparison because it’s always good from a reviewer’s perspective to understand how your work performs differently from others.”
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