GeM-NR performs multi-view consistent nonrigid editing by aligning depth-derived point clouds between edited and unedited scenes then refining projections conditioned on the original query view.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Proposes mCCDF plots to visualize ordinal regression results and communicate key takeaways from analyses of ordinal data like Likert scales.
citing papers explorer
-
GeM-NR: Geometry-Aware Multi-View Editing for Nonrigid Scene Changes
GeM-NR performs multi-view consistent nonrigid editing by aligning depth-derived point clouds between edited and unedited scenes then refining projections conditioned on the original query view.
-
Adapting CCDF Plots for Visualizing Ordinal Regression Results
Proposes mCCDF plots to visualize ordinal regression results and communicate key takeaways from analyses of ordinal data like Likert scales.