Recovering detailed geometry from high-resolution images is critical for precise perception of the surroundings and objects. However, existing methods which use latent-space modeling and VAE reconstruction can compromise geometric details. Furthermore, decoding from latent codes introduces substantial inference overhea...
Bo-Wen Chai, Tian-Bao Zhang, Shu-Yu Wu et al.· 0 citations
Drive-HWM is presented, a hierarchical slow--fast world modeling framework that organizes future representation prediction and action generation at complementary temporal scales and introduces Dynamic-Aware Latents learned through optical-flow prediction.
Zhao-Xin Fan, Tian-Bao Zhang, Wen-Jun Wu et al.· 0 citations
This work proposes VOP-Nav, a novel navigation system that combines the geometric safety of VO with the agile adaptability of end-to-end learning and validates the system's robustness and efficiency in complex indoor and outdoor dynamic environments.
LiteMVS is a lightweight multi-view depth estimation model that integrates plane-sweep geometric reasoning with strong monocular semantic and structural priors and employs a Mixture-of-Experts (MoE) formulation to enable adaptive geometric aggregation across depth hypotheses.
Tian-Bao Zhang, Zeyu Liu, Shuyu Wu et al.· 0 citations
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