Few-shot class-incremental learning (FSCIL) aims to learn novel classes from limited annotations while preserving prior knowledge. Existing methods typically assume a sufficiently large base session, but this assumption fails when both base and incremental data are scarce, leading to weak initial representations, seman...
Jun-Hui Yin, Yu-Chen Yang, Yi-Lin Yin et al.· 0 citations
Deriving vivid and expressive 3D human dance from music signals has gained tremendous progress in virtual avatar animation. Existing approaches typically overlook the diversity of human body shapes and generate dance motions using standardized body representations, without explicitly modeling the intrinsic relationship...
Mu-Yi Sun, Ze-Zhao Tian, Xing-Qun Qi et al.· International Journal of Com...· 0 citations
This work proposes a novel Rating-Aware Argument Generation framework designed to produce persuasive arguments aligned with fine-grained rating intensities, and demonstrates that this method is effective in improving rating alignment and mitigating rating drift.
Wenjie Hua, Quan Fang, Muyi Sun et al.· Multimedia Systems· 0 citations
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