Attention-DP3: Spatially Object-aware 3D Diffusion Policy via Geometry-aligned Attentional Conditioning
Attention-DP3 adds spatially object-aware attentional conditioning to 3D diffusion policies, improving robotic manipulation by up to 31% under heavy clutter.
Attention-DP3 injects object-level geometric cues into the unchanged DP3 diffusion policy via Tri-field Attentional Conditioning, using targetness, intra-target saliency, and backgroundness fields. Open-vocabulary 2D segmentation masks are lifted to 3D with calibrated camera geometry to build object-centric priors. Experiments on Adroit, DexArt, MetaWorld, and a real-world SO101 platform show state-of-the-art results, outperforming DP3 by up to 31% under heavy distractor clutter; the code is publicly available on GitHub.
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