Learning manipulation from human video requires high-fidelity hand-motion reconstruction in metric units. Today's metric hand labels come from studio rigs and instrumented headsets, and both are confined in the same two ways: neither leaves a prepared setting, and neither is checked against an independent reference. Un...
Jian-Gong Xiao, Zhi-Hao Zhang, Yi-Fei Dong et al.· 0 citations
Despite its crucial role in video object removal (VOR), existing evaluation paradigms face two critical limitations: questionable references and a misalignment between tradi- tional metrics and human preference. To address these challenges, we introduce VOR- Bench, which advances VOR evaluation through three integrated...
Hao-Nan Huang, Tian-Rui Qiu, Xiang-Hao Zang et al.· 0 citations
Transformers outperform traditional neural networks but face high computational and memory costs, limiting edge device deployment. Although many hardware accelerators aim to address this, the original Transformer structure still restricts the optimization effect. A recent breakthrough, mixture-of-depths (MoDs), employs...
Jia-Ning Chen, Wen-Long Ma, Yun-Chuan Li et al.· IEEE Transactions on Very La...· 0 citations
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