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October 12, 2025Open Access

CausNVS: Autoregressive Multi-view Diffusion for Flexible 3D Novel View Synthesis

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CausNVS improves the generation of novel views by supporting arbitrary input-output configurations.
The model utilizes causal masking and pairwise-relative camera pose encodings for effective camera control.
At inference, the approach combines spatial techniques and noise conditioning to minimize drift.
Experiments reveal CausNVS consistently achieves high visual quality across various camera trajectories.

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New autoregressive framework enhances flexibility in 3D novel view synthesis, suggesting broader application potential.

Kong et al. (2025) studied this question.

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