Compared with relying solely on initial observations and language instructions, predicting goal images with generative models as high-level visual guidance can significantly enhance the robustness of Vision-Language-Action (VLA) models. However, most existing foundation models have not systematically incorporated goal...
Xiao-Yuan Fang, Shuo Feng, Yuxuan Wang et al.· 0 citations
Action-conditioned cloth dynamics prediction requires both locally plausible deformation and long-range coordination. Existing approaches largely follow two paradigms. Mesh-based GNNs capture local physical responses through material connectivity. However, their finite message-passing range limits coordination between...
Zi-Hang Wang, Jian-Ming Hu, Shang Su et al.· 0 citations
Copper-Policy is introduced, which learns a compact World representation with the policy rather than relying on a predefined target space and predicts future observation embeddings conditioned on task intention without reconstructing pixels through temporal joint-embedding prediction.
Ze Feng, Yi-Xu Feng, Ling-Yu Xiao et al.· 0 citations
Experimental results on REVERIE and SOON datasets demonstrate that ViSMoE outperforms the previous state-of-the-art methods, showing the superiority of the proposed method.
Shuo Feng, Pi-Ji Li· International Conference on...· 0 citations
This work proposes a self-evolving method that reduces failure rates by 51--67% relative to trained baselines and by 8-25% relative to state-of-the-art vision-language-action models after replacing redundant nominal scenarios with diverse failure-prone ones.
Linxuan He, Yuying Tian, Ling-Xiang Fan et al.· arXiv.org· 0 citations
AirAlign is proposed, a framework for RGB-only image-pair relative pose alignment for UAVs, using a pretrained visual geometry reconstruction model as the backbone to extract geometry-aware features from source-target image pairs.
Jin-Yi Zhou, Shuo Feng, Yufei Wu et al.· 0 citations
This work proposes DC-WAM, a dynamic-centric WAM framework that redistributes supervision and computation in the RGB video branch that consistently improves policy performance, especially under out-of-distribution perturbations in lighting, object appearance, and background texture.
Haoyuan Ji, Lingxiang Fan, Shang Su et al.· 0 citations
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