AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The proposed World-Model Alignment for Latent Trajectories (WALT), which learns a compact generative trajectory latent space by transferring information from a frozen pretrained driving world model without modifying the world model itself, is proposed.
This work proposes Robust Semantic-aware Gaussian Splatting SLAM (RoSe-SLAM), to address the dynamic challenge by a holistic semantic scene understanding from uncalibrated monocular inputs, achieving accurate camera tracking and high-quality geometry reconstruction.
This work proposes SaLon3R, a novel framework for Structure-aware, Long-term 3DGS Reconstruction that effectively prunes the redundant 3DGS and resolves artifacts in a single feed-forward pass, and introduces a 3D Point Transformer to overcome geometric inconsistencies caused by long-term accumulative errors.
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