6 papers · 1 filter
Human4K: A Large-Scale 4K Multi-View Mocap Dataset for Whole-Body 3D Human Reconstruction
Tianshun Han, Ziyu Shi, Lijian Liu +7
Recent advances in 3D human reconstruction have improved overall performance, yet current models still fail in the most challenging real-world scenarios. They often produce unstabl…
EmbryoDiff: A Conditional Diffusion Framework with Multi-Focal Feature Fusion for Fine-Grained Embryo Developmental Stage Recognition
Yong Sun, Zhengjie Zhang, Junyu Shi +3
Identification of fine-grained embryo developmental stages during In Vitro Fertilization (IVF) is crucial for assessing embryo viability. Although recent deep learning methods have…
MoGIC: Boosting Motion Generation via Intention Understanding and Visual Context
Junyu Shi, Yong Sun, Zhiyuan Zhang +4
Existing text-driven motion generation methods often treat synthesis as a bidirectional mapping between language and motion, but remain limited in capturing the causal logic of act…
GenM: Generative Pretrained Multi-path Motion Model for Text Conditional Human Motion Generation
Junyu Shi, Lijiang Liu, Yong Sun +3
Scaling up motion datasets is crucial to enhance motion generation capabilities. However, training on large-scale multi-source datasets introduces data heterogeneity challenges due…
MoReFun: Past-Movement Guided Motion Representation Learning for Future Motion Prediction and Understanding
Junyu Shi, Haoting Wu, Zhiyuan Zhang +3
3D human motion prediction aims to generate coherent future motions from observed sequences, yet existing end-to-end regression frameworks often fail to capture complex dynamics an…
PMMTalk: Speech-Driven 3D Facial Animation from Complementary Pseudo Multi-modal Features
Tianshun Han, Shengnan Gui, Yiqing Huang +9
Speech-driven 3D facial animation has improved a lot recently while most related works only utilize acoustic modality and neglect the influence of visual and textual cues, leading…