ProJo4D uses progressive joint optimization to solve sparse-view inverse physics estimation, outperforming prior methods with up to 10x better geometric accuracy in 4D state prediction and material estimation.
PAC-neRF: Physics augmented continuum neural radiance fields for geometry-agnostic system identification
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
ProJo4D: Progressive Joint Optimization for Sparse-View Inverse Physics Estimation
ProJo4D uses progressive joint optimization to solve sparse-view inverse physics estimation, outperforming prior methods with up to 10x better geometric accuracy in 4D state prediction and material estimation.