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20202025
most citedAFTer-UNet: Axial Fusion Transformer UNet for Medical Image Segmentation

11 citations · 20 across the 6 of their papers we have counts for

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9 papers · 1 filter

cs.CV2025

MoME: Mixture of Visual Language Medical Experts for Medical Imaging Segmentation

Arghavan Rezvani, Xiangyi Yan, Anthony T. Wu +3

In this study, we propose MoME, a Mixture of Visual Language Medical Experts, for Medical Image Segmentation. MoME adapts the successful Mixture of Experts (MoE) paradigm, widely u…

cs.CV2023

CVTHead: One-shot Controllable Head Avatar with Vertex-feature Transformer

Haoyu Ma, Tong Zhang, Shanlin Sun +3

Reconstructing personalized animatable head avatars has significant implications in the fields of AR/VR. Existing methods for achieving explicit face control of 3D Morphable Models…

cs.CV20231 cited

Hybrid-CSR: Coupling Explicit and Implicit Shape Representation for Cortical Surface Reconstruction

Shanlin Sun, Thanh-Tung Le, Chenyu You +6

We present Hybrid-CSR, a geometric deep-learning model that combines explicit and implicit shape representations for cortical surface reconstruction. Specifically, Hybrid-CSR begin…

cs.CV2023

Localized Region Contrast for Enhancing Self-Supervised Learning in Medical Image Segmentation

Xiangyi Yan, Junayed Naushad, Chenyu You +6

Recent advancements in self-supervised learning have demonstrated that effective visual representations can be learned from unlabeled images. This has led to increased interest in…

cs.CV20221 cited

Identity-Aware Hand Mesh Estimation and Personalization from RGB Images

Deying Kong, Linguang Zhang, Liangjian Chen +6

Reconstructing 3D hand meshes from monocular RGB images has attracted increasing amount of attention due to its enormous potential applications in the field of AR/VR. Most state-of…

cs.CV20222 cited

PPT: token-Pruned Pose Transformer for monocular and multi-view human pose estimation

Haoyu Ma, Zhe Wang, Yifei Chen +6

Recently, the vision transformer and its variants have played an increasingly important role in both monocular and multi-view human pose estimation. Considering image patches as to…