StippleDiffusion is a late-stage denoising ControlNet on an optimal-transport point-set diffusion baseline that produces capacity-constrained stipples from arbitrary density maps, generalizes to unseen point budgets, and matches optimization baselines on Icons-50 while remaining end-to-end trainable
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2 Pith papers cite this work. Polarity classification is still indexing.
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ViVo introduces a diverse multi-view volumetric video dataset with raw multi-camera RGB-depth data, calibration, masks, and point clouds to support reconstruction and compression research, with benchmarks highlighting limitations of current methods.
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StippleDiffusion: Capacity-Constrained Stippling using Controlled Diffusion
StippleDiffusion is a late-stage denoising ControlNet on an optimal-transport point-set diffusion baseline that produces capacity-constrained stipples from arbitrary density maps, generalizes to unseen point budgets, and matches optimization baselines on Icons-50 while remaining end-to-end trainable
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ViVo: A Dataset for Volumetric Video Reconstruction and Compression
ViVo introduces a diverse multi-view volumetric video dataset with raw multi-camera RGB-depth data, calibration, masks, and point clouds to support reconstruction and compression research, with benchmarks highlighting limitations of current methods.