most citedHuman Joint Kinematics Diffusion-Refinement for Stochastic Motion Prediction

2 citations · 6 across the 6 of their papers we have counts for

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cs.CV2023★ 1 cited

Enhanced Fine-grained Motion Diffusion for Text-driven Human Motion Synthesis

Dong Wei, Xiaoning Sun, Huaijiang Sun +4

The emergence of text-driven motion synthesis technique provides animators with great potential to create efficiently. However, in most cases, textual expressions only contain gene…

cs.CV2023

DeFeeNet: Consecutive 3D Human Motion Prediction with Deviation Feedback

Xiaoning Sun, Huaijiang Sun, Bin Li +3

Let us rethink the real-world scenarios that require human motion prediction techniques, such as human-robot collaboration. Current works simplify the task of predicting human moti…

cs.CV2023

Meta-Auxiliary Learning for Adaptive Human Pose Prediction

Qiongjie Cui, Huaijiang Sun, Jianfeng Lu +2

Predicting high-fidelity future human poses, from a historically observed sequence, is decisive for intelligent robots to interact with humans. Deep end-to-end learning approaches,…

cs.CV2022★ 2 cited

Human Joint Kinematics Diffusion-Refinement for Stochastic Motion Prediction

Dong Wei, Huaijiang Sun, Bin Li +4

Stochastic human motion prediction aims to forecast multiple plausible future motions given a single pose sequence from the past. Most previous works focus on designing elaborate l…

cs.CV2022★ 1 cited

Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction

Xiaoning Sun, Qiongjie Cui, Huaijiang Sun +3

Previous works on human motion prediction follow the pattern of building a mapping relation between the sequence observed and the one to be predicted. However, due to the inherent…