4 citations · 8 across the 9 of their papers we have counts for
9 papers
Resolving Inconsistent Semantics in Multi-Dataset Image Segmentation
Qilong Zhangli, Di Liu, Abhishek Aich +2
Leveraging multiple training datasets to scale up image segmentation models is beneficial for increasing robustness and semantic understanding. Individual datasets have well-define…
Layout Agnostic Scene Text Image Synthesis with Diffusion Models
Qilong Zhangli, Jindong Jiang, Di Liu +6
While diffusion models have significantly advanced the quality of image generation their capability to accurately and coherently render text within these images remains a substanti…
DeFormer: Integrating Transformers with Deformable Models for 3D Shape Abstraction from a Single Image
Di Liu, Xiang Yu, Meng Ye +4
Accurate 3D shape abstraction from a single 2D image is a long-standing problem in computer vision and graphics. By leveraging a set of primitives to represent the target shape, re…
Deep Deformable Models: Learning 3D Shape Abstractions with Part Consistency
Di Liu, Long Zhao, Qilong Zhangli +3
The task of shape abstraction with semantic part consistency is challenging due to the complex geometries of natural objects. Recent methods learn to represent an object shape usin…
Improving Tuning-Free Real Image Editing with Proximal Guidance
Ligong Han, Song Wen, Qi Chen +13
DDIM inversion has revealed the remarkable potential of real image editing within diffusion-based methods. However, the accuracy of DDIM reconstruction degrades as larger classifie…
Dealing With Heterogeneous 3D MR Knee Images: A Federated Few-Shot Learning Method With Dual Knowledge Distillation
Xiaoxiao He, Chaowei Tan, Bo Liu +8
Federated Learning has gained popularity among medical institutions since it enables collaborative training between clients (e.g., hospitals) without aggregating data. However, due…
DeepRecon: Joint 2D Cardiac Segmentation and 3D Volume Reconstruction via A Structure-Specific Generative Method
Qi Chang, Zhennan Yan, Mu Zhou +8
Joint 2D cardiac segmentation and 3D volume reconstruction are fundamental to building statistical cardiac anatomy models and understanding functional mechanisms from motion patter…
TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers
Di Liu, Yunhe Gao, Qilong Zhangli +8
Combining information from multi-view images is crucial to improve the performance and robustness of automated methods for disease diagnosis. However, due to the non-alignment char…
Region Proposal Rectification Towards Robust Instance Segmentation of Biological Images
Qilong Zhangli, Jingru Yi, Di Liu +10
Top-down instance segmentation framework has shown its superiority in object detection compared to the bottom-up framework. While it is efficient in addressing over-segmentation, t…