2 citations · 2 across the 8 of their papers we have counts for
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TAT: Task-Adaptive Transformer for All-in-One Medical Image Restoration
Zhiwen Yang, Jiaju Zhang, Yang Yi +3
Medical image restoration (MedIR) aims to recover high-quality medical images from their low-quality counterparts. Recent advancements in MedIR have focused on All-in-One models ca…
Novel View Synthesis from A Few Glimpses via Test-Time Natural Video Completion
Yan Xu, Yixing Wang, Stella X. Yu
Given just a few glimpses of a scene, can you imagine the movie playing out as the camera glides through it? That's the lens we take on \emph{sparse-input novel view synthesis}, no…
All-in-One Medical Image Restoration with Latent Diffusion-Enhanced Vector-Quantized Codebook Prior
Haowei Chen, Zhiwen Yang, Haotian Hou +4
All-in-one medical image restoration (MedIR) aims to address multiple MedIR tasks using a unified model, concurrently recovering various high-quality (HQ) medical images (e.g., MRI…
FEAT: Full-Dimensional Efficient Attention Transformer for Medical Video Generation
Huihan Wang, Zhiwen Yang, Hui Zhang +3
Synthesizing high-quality dynamic medical videos remains a significant challenge due to the need for modeling both spatial consistency and temporal dynamics. Existing Transformer-b…