3 papers
eess.IV2026
MoRE: A Mixture-of-Experts-Based Task-Adaptive End-to-End Network for Multimodal MRI Reconstruction
Yuyang Li, Yipin Deng, Wenlei Shang +4
Although accelerated MRI reconstruction has advanced rapidly through end-to-end learning, deploying a single unified network that generalizes across diverse anatomies and contrasts…
cs.CV2026
L2A: Learning to Accumulate Pose History for Accurate 3D Human Pose Estimation
Zehua Wang, Changwang Mei, Huaijiang Sun +2
Existing 2D-3D lifting human pose estimation methods have achieved strong performance. But the utilization of historical pose representations across network depth was overlooked. I…
eess.IV2025
Branch Learning in MRI: More Data, More Models, More Training
Yuyang Li, Yipin Deng, Zijian Zhou +1
We investigated two complementary strategies for multicontrast cardiac MR reconstruction: physics-consistent data-space augmentation (DualSpaceCMR) and parameter-efficient capacity…