most citedWHALES: A Multi-Agent Scheduling Dataset for Enhanced Cooperation in Autonomous Driving

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Adaptive Conditional Contrast-Agnostic Deformable Image Registration with Uncertainty Estimation

Yinsong Wang, Xinzhe Luo, Siyi Du +1

Deformable multi-contrast image registration is a challenging yet crucial task due to the complex, non-linear intensity relationships across different imaging contrasts. Convention…

cs.CV2026

Self-Supervised Slice-to-Volume Reconstruction with Gaussian Representations for Fetal MRI

Yinsong Wang, Thomas Fletcher, Xinzhe Luo +3

Reconstructing 3D fetal MR volumes from motion-corrupted stacks of 2D slices is a crucial and challenging task. Conventional slice-to-volume reconstruction (SVR) methods are time-c…

cs.CV2024★ 1 cited

WHALES: A Multi-Agent Scheduling Dataset for Enhanced Cooperation in Autonomous Driving

Yinsong Wang, Siwei Chen, Ziyi Song +1

Cooperative perception research is hindered by the limited availability of datasets that capture the complexity of real-world Vehicle-to-Everything (V2X) interactions, particularly…

eess.IV2024

SGSR: Structure-Guided Multi-Contrast MRI Super-Resolution via Spatio-Frequency Co-Query Attention

Shaoming Zheng, Yinsong Wang, Siyi Du +1

Magnetic Resonance Imaging (MRI) is a leading diagnostic modality for a wide range of exams, where multiple contrast images are often acquired for characterizing different tissues.…

cs.CV2024

CAR: Contrast-Agnostic Deformable Medical Image Registration with Contrast-Invariant Latent Regularization

Yinsong Wang, Siyi Du, Shaoming Zheng +2

Multi-contrast image registration is a challenging task due to the complex intensity relationships between different imaging contrasts. Conventional image registration methods are…

cs.CV2024

TIP: Tabular-Image Pre-training for Multimodal Classification with Incomplete Data

Siyi Du, Shaoming Zheng, Yinsong Wang +3

Images and structured tables are essential parts of real-world databases. Though tabular-image representation learning is promising to create new insights, it remains a challenging…