AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work proposes a motion-aware 3D smoothing filter specifically designed for 4D representations that adapts the filter strength based on local motion information, effectively mitigating aliasing without compromising rendering quality.
This work introduces Principia, a benchmark that evaluates Newtonian physics through relational consistency between paired objects, and introduces a calibration-independent consistency score that quantifies physical violation directly in image space.
This work proposes a novel approach to explicitly control the number of Gaussians by leveraging local texture information through three key components: texture estimation to capture spatial variation in scene detail, texture-aware pruning that removes redundant Gaussians from low frequency regions, and an adaptive Gaus...
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