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arXiv preprint arXiv:2601.14674 (2026) 6

3 Pith papers cite this work. Polarity classification is still indexing.

3 Pith papers citing it

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cs.CV 3

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representative citing papers

Probing into Camera Control of Video Models

cs.CV · 2026-05-14 · unverdicted · novelty 7.0

A training-free method reformulates camera control as geometric displacement fields applied via differentiable latent resampling, enabling control and bias probing in video diffusion models.

Syn4D: A Multiview Synthetic 4D Dataset

cs.CV · 2026-05-06 · unverdicted · novelty 5.0

Syn4D is a new multiview synthetic 4D dataset supplying dense ground-truth annotations for dynamic scene reconstruction, tracking, and human pose estimation.

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Showing 3 of 3 citing papers after filters.

  • Probing into Camera Control of Video Models cs.CV · 2026-05-14 · unverdicted · none · ref 49

    A training-free method reformulates camera control as geometric displacement fields applied via differentiable latent resampling, enabling control and bias probing in video diffusion models.

  • VolFill: Single-View Amodal 3D Scene Reconstruction with Volumetric Flow Matching cs.CV · 2026-05-29 · unverdicted · none · ref 86

    VolFill uses a hybrid 3D VAE to compress sparse truncated unsigned distance function grids into latent space and a latent Diffusion Transformer to denoise complete scenes, conditioned on geometry foundation models, outperforming baselines on SCRREAM and NRGB-D datasets.

  • Syn4D: A Multiview Synthetic 4D Dataset cs.CV · 2026-05-06 · unverdicted · none · ref 123

    Syn4D is a new multiview synthetic 4D dataset supplying dense ground-truth annotations for dynamic scene reconstruction, tracking, and human pose estimation.