AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A biologically inspired framework for learning object-centric visual representations in an unsupervised manner, suggesting that motion-induced object representations offer a compelling alternative to existing vision foundation models, capturing a crucial but overlooked level of abstraction: the visual instance.
A Geometry-grounded Unified 3D Perception (GeoUP) framework that adapts the reconstruction-oriented latent of VGGT to calibrated, streaming multi-camera driving scenes and achieves SOTA performance across detection, occupancy, and depth estimation is presented.
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