TACO reformulates neural implicit mapping as temporal consensus optimization to enable continual adaptation to scene changes without data replay or storage.
On the linear convergence of the admm in de- centralized consensus optimization.IEEE Transactions on Signal Processing, 62(7):1750–1761, 2014
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TACO: Temporal Consensus Optimization for Continual Neural Mapping
TACO reformulates neural implicit mapping as temporal consensus optimization to enable continual adaptation to scene changes without data replay or storage.