2026
Spatially-Adaptive Gradient Re-parameterization for 3D Large Kernel Optimization
ICML 2026poster
Large kernel convolutions offer a scalable alternative to vision transformers for high-resolution 3D volumetric analysis, yet naïvely increasing kernel size often leads to optimization instability. Motivated by the spatial bias inherent in effective receptive fields (ERFs), we theoretically demonstr…