Cost-Efficient Multi-Scale Fovea for Semantic-Based Visual Search Attention

ArXi:2604.03836v1 Announce Type: cross Semantics are one of the primary sources of top-down preattentive information. Modern deep object detectors excel at extracting such valuable semantic cues from complex visual scenes. However, the size of the visual input to be processed by these detectors can become a bottleneck, particularly in terms of time costs, affecting an artificial attention system's biological plausibility and real-time deployability.