Published and submitted research by Weiping Yan, with official publication and submission links.
This page lists one formally published paper and one manuscript submitted to DAI 2026. The submitted manuscript is under review and its decision is pending; it is not yet accepted or published. The 2023 independent study used randomly generated, synthetic data; it did not analyze clinical records or real-world environmental observations. Official titles and metadata are retained in their original language.
Reconstructing sharp and animatable 3D human avatars from motion-blurred videos remains challenging under partial occlusion, where unreliable SMPL estimates can propagate pose errors into Gaussian deformation. To address this problem, we propose OAM-GA, an occlusion-robust framework for motion-aware Gaussian avatar reconstruction. OAM-GA estimates joint-wise reliability and restores missing motion using visible temporal context. Specifically, a Bidirectional Wavelet Masked Motion Completion module decomposes motion features into low- and high-frequency components and reconstructs contiguous occluded intervals from observations before and after the masked region. Clean–occluded contrastive consistency learning further encourages occlusion-invariant motion representations, while reliability-guided residual refinement selectively corrects uncertain joints and preserves reliable ones. Experiments on BlurZJU and BS-Human show that OAM-GA improves overall reconstruction robustness and perceptual quality under diverse occlusion patterns while maintaining the rendering fidelity of the original baseline.
@unpublished{wang2026oamga,title={{OAM-GA}: Reliability-Guided Motion Completion for Occlusion-RobustGaussian Avatars},author={Wang, Xiang and Yan, Xu and Pei, Letian and Yan, Weiping},year={2026},note={Submitted to {DAI} 2026; under review, decision pending, and not yet accepted or published.},url={https://openreview.net/forum?id=UV2UJ4VHf7},}
@article{yan2023pm25,title={Effect of {PM2.5} air pollution on the incidence of respiratory diseases: A {Python}-based data analysis},author={Yan, Weiping},journal={Theoretical and Natural Science},volume={8},number={1},pages={70--75},year={2023},month=nov,publisher={EWA Publishing},doi={10.54254/2753-8818/8/20240361},url={https://tns.ewapub.com/article/view/6279},}