AWhat changed
Learned input-dependent offsets for convolution and region pooling, then expanded deformable layers with modulation scalars and R-CNN feature-mimicking supervision to improve spatial adaptation.
Scientific scope
Learned input-dependent offsets for convolution and region pooling, then expanded deformable layers with modulation scalars and R-CNN feature-mimicking supervision to improve spatial adaptation. Chronological two-paper family with separate contributors. Bilinear resampling and earlier spatial-transform methods are inherited. Learned offsets do not certify geometric invariance, object-only receptive support or physically meaningful deformation; v2 explicitly notes offset visualizations can mislead. Feature mimicking is an auxiliary training resource, not free supervision.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Chronological two-paper family with separate contributors. Bilinear resampling and earlier spatial-transform methods are inherited. Learned offsets do not certify geometric invariance, object-only receptive support or physically meaningful deformation; v2 explicitly notes offset visualizations can mislead. Feature mimicking is an auxiliary training resource, not free supervision.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
Full scientific record · Browse contribution grades · Request a correction