activity
20152023
most citedNon-Local Recurrent Network for Image Restoration

268 citations · 1.3k across the 43 of their papers we have counts for

collaborators

43 papers

cs.CV2023

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…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 2 cited

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…

cs.LG2023★ 2 cited

Graph Analysis Using a GPU-based Parallel Algorithm: Quantum Clustering

Zhe Wang, ZhiJie He, Ding Liu

The article introduces a new method for applying Quantum Clustering to graph structures. Quantum Clustering (QC) is a novel density-based unsupervised learning method that determin…

cs.CV2023★ 30 cited

Hierarchical Integration Diffusion Model for Realistic Image Deblurring

Zheng Chen, Yulun Zhang, Ding Liu +4

Diffusion models (DMs) have recently been introduced in image deblurring and exhibited promising performance, particularly in terms of details reconstruction. However, the diffusio…

eess.IV2023

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…