Papers by Kunhang Li

2 papers
Motion Generation from Fine-grained Textual Descriptions (2024.lrec-main)

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Challenge: Existing models for motion generation from textual descriptions are limited to coarse-grained descriptions.
Approach: They build a large-scale language-motion dataset specializing in fine-grained textual descriptions . they feed it with step-by-step instructions with pseudo-code compulsory checks . quantitative evaluation shows that the model outperforms MotionDiffuse in generating spatially or chronologically composite motions .
Outcome: The proposed model outperforms existing models in generating human motion sequences from textual descriptions by a large margin.
How Much Do Large Language Models Know about Human Motion? A Case Study in 3D Avatar Control (2025.findings-emnlp)

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Challenge: a new study explores the human motion knowledge of Large Language Models (LLMs) using 3D avatar control.
Approach: They use 20 representative motion instructions to interpolate LLMs into avatar animations . they find they are strong at interpreting high-level body movements but struggle with precise body part positioning .
Outcome: The proposed model is strong at interpreting high-level body movements but struggles with precise body part positioning.

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