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AnchorDream: Repurposing Video Diffusion for Embodiment-Aware Robot Data Synthesis

Description

The collection of large-scale and diverse robot demonstrations remains a major bottleneck for imitation learning, as real-world data acquisition is costly and simulators offer limited diversity and fidelity with pronounced sim-to-real gaps. While generative models present an attractive solution, existing methods often alter only visual appearances without creating new behaviors, or suffer from embodiment inconsistencies that yield implausible motions. To address these limitations, we introduce A

Source

http://arxiv.org/abs/2512.11797v1