AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
We have 3 of 16 papers
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
This work proposes \textbf{novel-view semantic rendering} as an auxiliary training task that requires the model to predict the semantic layout of an unobserved viewpoint, inspired by humans'ability to mentally simulate novel viewpoints during spatial reasoning.
SAM-V introduces a prompt-fusion mechanism that enriches sparse SAM prompt tokens with view-specific camera tokens and local VGGT features, making the prompt representation both view-aware and spatially grounded, together with a mask decoder that attends to dense 2D and 3D features.
ReToken is a single learnable embedding trained as an explicit retrieval target that selects a sparse set of query-relevant visual tokens from a pre-filled visual KV cache that yields consistent gains across image and video benchmarks.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.