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By mining cross-domain category relationships, this method significantly improves open-set object detection, enabling models to adapt to new object categories without target annotations.
Square superpixels, generated via granular ball computing, unlock efficient parallel processing and end-to-end optimization in deep learning pipelines by replacing irregular shapes with multi-scale square blocks.
Current LMMs can't reliably turn complex images into code, failing to preserve structural integrity even in relatively simple scenarios, as shown by the new Omni-I2C benchmark.
