Unverified50% confidenceFactExact time
The paper conducted experiments on datasets such as ACID, and the results show that CoTL's compact, unstructured Token set not only supports competitive novel-view synthesis but can also serve as a latent space for generative models to generate 3D Gaussian scenes.
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10/14/2026
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UnverifiedCoTL (Compact Token Learning) proposes using a small set of compact latent Tokens to preserve the geometric and appearance information of a scene, allowing representation capacity to scale naturally with the number of observations.73% similarUnverifiedAllowing the model to freely generate coordinates and styles tends to cause problems such as element overlap and misaligned connections, and it is usually necessary to provide canvas specifications and layout conventions and use an intermediate layer for coordinate correction.70% similarUnverifiedSketch-to-simulation requires the model to simultaneously coordinate three capabilities: image understanding, spatial reasoning, and physics modeling.68% similarUnverifiedMainstream strategies for handling 3D CT volumetric data include proportional downsampling, block-wise processing followed by feature aggregation, and using 3D convolutional networks to first extract spatial representations before connecting to a language model.68% similarUnverifiedNative 3D diffusion methods offer superior geometric fidelity and cross-view consistency, but their bottleneck lies in the scarcity of large-scale 3D scene datasets.68% similar
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