12 papers
What is the Better Curriculum: Controller-Shaped Grasping Behavior for Contact Force-Sensitive Manipulation
Ziyan Feng, Zizhao Yuan, Yulong Fu +6
How should a robot learn to manipulate objects so fragile that sub-Newton contact forces can cause irreversible damage? Existing visuo-tactile policy learning typically treats tact…
Towards Exploratory and Focused Manipulation with Bimanual Active Perception: A New Problem, Benchmark and Strategy
Yuxin He, Ruihao Zhang, Tianao Shen +2
Recently, active vision has reemerged as an important concept for manipulation, since visual occlusion occurs more frequently when main cameras are mounted on the robot heads. We r…
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…
HGFreNet: Hop-hybrid GraphFomer for 3D Human Pose Estimation with Trajectory Consistency in Frequency Domain
Kai Zhai, Ziyan Huang, Qiang Nie +2
2D-to-3D human pose lifting is a fundamental challenge for 3D human pose estimation in monocular video, where graph convolutional networks (GCNs) and attention mechanisms have prov…
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…
RMG: Real-Time Expressive Motion Generation with Self-collision Avoidance for 6-DOF Companion Robotic Arms
Jiansheng Li, Haotian Song, Jinni Zhou +2
The six-degree-of-freedom (6-DOF) robotic arm has gained widespread application in human-coexisting environments. While previous research has predominantly focused on functional mo…
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…
3D Dynamics-Aware Manipulation: Endowing Manipulation Policies with 3D Foresight
Yuxin He, Ruihao Zhang, Xianzu Wu +3
The incorporation of world modeling into manipulation policy learning has pushed the boundary of manipulation performance. However, existing efforts simply model the 2D visual dyna…
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…