Spatial Residual for Underwater Object Detection

Feature drift is caused by the dynamic coupling of target features and degradation factors, which reduce underwater detector performance. We redefine feature drift as the instability of target features within boundary constraints while solving partial differential equations (PDEs). From this insight, we propose the Spatial Residual (SR) block, which uses SkipCut to establish effective constraints across the network width for solving PDEs and optimizes the solution space. It is implemented as a general-purpose backbone with 5 Spatial Residuals (BSR5) for complex feature scenarios. Specifically, BSR5 extracts discrete channel slices through SkipCut, where each sliced feature is parsed within the appropriate data…

• NN
  National Natural Science Foundation of China

  Awards: 62301105, 62301107