MSACT improves localization stability and task success rates in limited-data bimanual manipulation by extracting stable 2D attention points and aligning predicted attention sequences across frames without keypoint labels.
3d space perception via disparity learning using stereo images and an attention mechanism: Real-time grasping motion generation for transparent objects
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
A stereo multistage spatial attention deep predictive learning system improves robustness and success rates for real-time mobile manipulation under visual scale variation and disturbances.
citing papers explorer
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MSACT: Multistage Spatial Alignment for Stable Low-Latency Fine Manipulation
MSACT improves localization stability and task success rates in limited-data bimanual manipulation by extracting stable 2D attention points and aligning predicted attention sequences across frames without keypoint labels.
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Stereo Multistage Spatial Attention for Real-Time Mobile Manipulation Under Visual Scale Variation and Disturbances
A stereo multistage spatial attention deep predictive learning system improves robustness and success rates for real-time mobile manipulation under visual scale variation and disturbances.