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Hi, BiRefNet and InSPyReNet use higher resolution input images (e.g., 1024×1024) and more advanced decoder designs, so they may achieve more accurate results. Theoretically, the performance of SAM2-UNet can be further improved if it is directly extended to high resolution as well. However, since the standard U-Net decoder is not designed to handle high-resolution images, this improvement may be very limited. You can try to modify the SAM2-UNet decoder to get better results.
How is it different from rgb salient object detection models like birefnet, inspyrenet:
https://paperswithcode.com/sota/salient-object-detection-on-dut-omron.
Do these models have better accuracy than SAM2-UNet for general purpose usage?
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