VDPP is an RGB-free video depth post-processor that achieves over 43 FPS on Jetson Orin Nano by refining geometry at low resolution rather than reconstructing full scenes.
Depth map prediction from a single image using a multi-scale deep net- work.Advances in neural information processing systems, 27
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
The paper proposes information scope as a new interpretability axis for SAE features in CLIP and introduces the Contextual Dependency Score to separate local from global scope features, showing they influence model predictions differently.
citing papers explorer
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VDPP: Video Depth Post-Processing for Speed and Scalability
VDPP is an RGB-free video depth post-processor that achieves over 43 FPS on Jetson Orin Nano by refining geometry at low resolution rather than reconstructing full scenes.
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Beyond Semantics: Disentangling Information Scope in Sparse Autoencoders for CLIP
The paper proposes information scope as a new interpretability axis for SAE features in CLIP and introduces the Contextual Dependency Score to separate local from global scope features, showing they influence model predictions differently.