Sign Language Video Anonymization

no code implementations • SignLang (LREC) 2022 • Zhaoyang Xia, Yuxiao Chen, Qilong Zhangli, Matt Huenerfauth, Carol Neidle, Dimitri Metaxas

We modify a motion-based image animation model to generate high-resolution videos with the signer identity changed, but with the preservation of linguistically significant motions and facial expressions.

Image Animation Optical Flow Estimation

DeFormer: Integrating Transformers with Deformable Models for 3D Shape Abstraction from a Single Image

no code implementations • ICCV 2023 • Di Liu, Xiang Yu, Meng Ye, Qilong Zhangli, Zhuowei Li, Zhixing Zhang, Dimitris N. Metaxas

Accurate 3D shape abstraction from a single 2D image is a long-standing problem in computer vision and graphics.

Deep Deformable Models: Learning 3D Shape Abstractions with Part Consistency

no code implementations • 2 Sep 2023 • Di Liu, Long Zhao, Qilong Zhangli, Yunhe Gao, Ting Liu, Dimitris N. Metaxas

The task of shape abstraction with semantic part consistency is challenging due to the complex geometries of natural objects.

Improving Tuning-Free Real Image Editing with Proximal Guidance

1 code implementation • 8 Jun 2023 • Ligong Han, Song Wen, Qi Chen, Zhixing Zhang, Kunpeng Song, Mengwei Ren, Ruijiang Gao, Anastasis Stathopoulos, Xiaoxiao He, Yuxiao Chen, Di Liu, Qilong Zhangli, Jindong Jiang, Zhaoyang Xia, Akash Srivastava, Dimitris Metaxas

Null-text inversion (NTI) optimizes null embeddings to align the reconstruction and inversion trajectories with larger CFG scales, enabling real image editing with cross-attention control.

Dealing With Heterogeneous 3D MR Knee Images: A Federated Few-Shot Learning Method With Dual Knowledge Distillation

1 code implementation • 25 Mar 2023 • Xiaoxiao He, Chaowei Tan, Bo Liu, Liping Si, Weiwu Yao, Liang Zhao, Di Liu, Qilong Zhangli, Qi Chang, Kang Li, Dimitris N. Metaxas

The supervised learning of the proposed method extracts features from limited labeled data in each client, while the unsupervised data is used to distill both feature and response-based knowledge from a national data repository to further improve the accuracy of the collaborative model and reduce the communication cost.

Federated Learning Few-Shot Learning +1

DeepRecon: Joint 2D Cardiac Segmentation and 3D Volume Reconstruction via A Structure-Specific Generative Method

no code implementations • 14 Jun 2022 • Qi Chang, Zhennan Yan, Mu Zhou, Di Liu, Khalid Sawalha, Meng Ye, Qilong Zhangli, Mikael Kanski, Subhi Al Aref, Leon Axel, Dimitris Metaxas

Joint 2D cardiac segmentation and 3D volume reconstruction are fundamental to building statistical cardiac anatomy models and understanding functional mechanisms from motion patterns.

3D Reconstruction 3D Shape Reconstruction +5

TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers

no code implementations • 21 Mar 2022 • Di Liu, Yunhe Gao, Qilong Zhangli, Ligong Han, Xiaoxiao He, Zhaoyang Xia, Song Wen, Qi Chang, Zhennan Yan, Mu Zhou, Dimitris Metaxas

Combining information from multi-view images is crucial to improve the performance and robustness of automated methods for disease diagnosis.

Image Segmentation Medical Image Segmentation +2

Region Proposal Rectification Towards Robust Instance Segmentation of Biological Images

no code implementations • 6 Mar 2022 • Qilong Zhangli, Jingru Yi, Di Liu, Xiaoxiao He, Zhaoyang Xia, Qi Chang, Ligong Han, Yunhe Gao, Song Wen, Haiming Tang, He Wang, Mu Zhou, Dimitris Metaxas

Top-down instance segmentation framework has shown its superiority in object detection compared to the bottom-up framework.

Instance Segmentation object-detection +4