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Learning to See Low-Light Images via Feature Domain Adaptation
Qirui Yang, Qihua Cheng, Huanjing Yue +3
Raw low light image enhancement (LLIE) has achieved much better performance than the sRGB domain enhancement methods due to the merits of raw data. However, the ambiguity between n…
A Comparative Study of Image Restoration Networks for General Backbone Network Design
Xiangyu Chen, Zheyuan Li, Yuandong Pu +4
Despite the significant progress made by deep models in various image restoration tasks, existing image restoration networks still face challenges in terms of task generality. An i…
Unifying Image Processing as Visual Prompting Question Answering
Yihao Liu, Xiangyu Chen, Xianzheng Ma +4
Image processing is a fundamental task in computer vision, which aims at enhancing image quality and extracting essential features for subsequent vision applications. Traditionally…
Towards Efficient SDRTV-to-HDRTV by Learning from Image Formation
Xiangyu Chen, Zheyuan Li, Zhengwen Zhang +6
Modern displays can render video content with high dynamic range (HDR) and wide color gamut (WCG). However, most resources are still in standard dynamic range (SDR). Therefore, tra…
MomentaMorph: Unsupervised Spatial-Temporal Registration with Momenta, Shooting, and Correction
Zhangxing Bian, Shuwen Wei, Yihao Liu +6
Tagged magnetic resonance imaging (tMRI) has been employed for decades to measure the motion of tissue undergoing deformation. However, registration-based motion estimation from tM…
A survey on deep learning in medical image registration: new technologies, uncertainty, evaluation metrics, and beyond
Junyu Chen, Yihao Liu, Shuwen Wei +5
Deep learning technologies have dramatically reshaped the field of medical image registration over the past decade. The initial developments, such as regression-based and U-Net-bas…
Efficient HDR Reconstruction from Real-World Raw Images
Qirui Yang, Yihao Liu, Qihua Cheng +3
The growing prevalence of high-resolution displays on edge devices has created a pressing need for efficient high dynamic range (HDR) imaging algorithms. However, most existing HDR…
Unknown Sniffer for Object Detection: Don't Turn a Blind Eye to Unknown Objects
Wenteng Liang, Feng Xue, Yihao Liu +2
The recently proposed open-world object and open-set detection have achieved a breakthrough in finding never-seen-before objects and distinguishing them from known ones. However, t…
Masked Image Training for Generalizable Deep Image Denoising
Haoyu Chen, Jinjin Gu, Yihao Liu +5
When capturing and storing images, devices inevitably introduce noise. Reducing this noise is a critical task called image denoising. Deep learning has become the de facto method f…
Deformable Cross-Attention Transformer for Medical Image Registration
Junyu Chen, Yihao Liu, Yufan He +1
Transformers have recently shown promise for medical image applications, leading to an increasing interest in developing such models for medical image registration. Recent advancem…
Spatially-varying Regularization with Conditional Transformer for Unsupervised Image Registration
Junyu Chen, Yihao Liu, Yufan He +1
In the past, optimization-based registration models have used spatially-varying regularization to account for deformation variations in different image regions. However, deep learn…
Automated Ventricle Parcellation and Evan's Ratio Computation in Pre- and Post-Surgical Ventriculomegaly
Yuli Wang, Anqi Feng, Yuan Xue +6
Normal pressure hydrocephalus~(NPH) is a brain disorder associated with enlarged ventricles and multiple cognitive and motor symptoms. The degree of ventricular enlargement can be…
A latent space for unsupervised MR image quality control via artifact assessment
Lianrui Zuo, Yuan Xue, Blake E. Dewey +3
Image quality control (IQC) can be used in automated magnetic resonance (MR) image analysis to exclude erroneous results caused by poorly acquired or artifact-laden images. Existin…
DRIMET: Deep Registration for 3D Incompressible Motion Estimation in Tagged-MRI with Application to the Tongue
Zhangxing Bian, Fangxu Xing, Jinglun Yu +6
Tagged magnetic resonance imaging~(MRI) has been used for decades to observe and quantify the detailed motion of deforming tissue. However, this technique faces several challenges…