6 papers
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…
Time-Lapse Video-Based Embryo Grading via Complementary Spatial-Temporal Pattern Mining
Yong Sun, Yipeng Wang, Junyu Shi +5
Artificial intelligence has recently shown promise in automated embryo selection for In-Vitro Fertilization (IVF). However, current approaches either address partial embryo evaluat…
ExoGait-MS: Learning Periodic Dynamics with Multi-Scale Graph Network for Exoskeleton Gait Recognition
Lijiang Liu, Junyu Shi, Yong Sun +4
Current exoskeleton control methods often face challenges in delivering personalized treatment. Standardized walking gaits can lead to patient discomfort or even injury. Therefore,…
RoboAct-CLIP: Video-Driven Pre-training of Atomic Action Understanding for Robotics
Zhiyuan Zhang, Yuxin He, Yong Sun +3
Visual Language Models (VLMs) have emerged as pivotal tools for robotic systems, enabling cross-task generalization, dynamic environmental interaction, and long-horizon planning th…
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…