11 papers
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…
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…
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…