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Xidian University
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Achieving up to 4.7x speedup in TGNN training without sacrificing accuracy could redefine performance benchmarks in dynamic graph applications.
SA-LIVO achieves competitive accuracy while operating 3.6-6.3x more efficiently in memory usage than existing LiDAR-visual odometry systems.
