3 citations · 13 across the 14 of their papers we have counts for
9 papers · 1 filter
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…
Light Field Diffusion for Single-View Novel View Synthesis
Yifeng Xiong, Haoyu Ma, Shanlin Sun +3
Single-view novel view synthesis (NVS), the task of generating images from new viewpoints based on a single reference image, is important but challenging in computer vision. Recent…
Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation with Meta-Learning
Yiming Zhang, Tianang Leng, Kun Han +1
While the Segment Anything Model (SAM) excels in semantic segmentation for general-purpose images, its performance significantly deteriorates when applied to medical images, primar…
On-the-Fly Guidance Training for Medical Image Registration
Yuelin Xin, Yicheng Chen, Shengxiang Ji +2
This study introduces a novel On-the-Fly Guidance (OFG) training framework for enhancing existing learning-based image registration models, addressing the limitations of weakly-sup…
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…
Hybrid Neural Diffeomorphic Flow for Shape Representation and Generation via Triplane
Kun Han, Shanlin Sun, Xiaohui Xie
Deep Implicit Functions (DIFs) have gained popularity in 3D computer vision due to their compactness and continuous representation capabilities. However, addressing dense correspon…
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction
Tung Le, Khai Nguyen, Shanlin Sun +3
Mesh deformation plays a pivotal role in many 3D vision tasks including dynamic simulations, rendering, and reconstruction. However, defining an efficient discrepancy between predi…
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…
MedGen3D: A Deep Generative Framework for Paired 3D Image and Mask Generation
Kun Han, Yifeng Xiong, Chenyu You +5
Acquiring and annotating sufficient labeled data is crucial in developing accurate and robust learning-based models, but obtaining such data can be challenging in many medical imag…