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existing 3D affordance learning methods struggle with generalization and robustness due to limited annotated data and a reliance on 3D backbones focused on geometric encoding, which often lack resilience to real-world noise and data corruption. We propose GEAL,...
In contrast, our frequency regularization, which can be seen as an implicit geometry regularization, forces smooth geome- try at the beginning (due to the limited frequency spectrum) 8259 Setting PSNR " SSIM " LPIPS # Average # 3-view 6-view 9-view 3...