no code implementations • 30 Apr 2024 • Yuekun Dai, Dafeng Zhang, Xiaoming Li, Zongsheng Yue, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Peiqing Yang, Zhezhu Jin, Guanqun Liu, Chen Change Loy, Lize Zhang, Shuai Liu, Chaoyu Feng, Luyang Wang, Shuan Chen, Guangqi Shao, Xiaotao Wang, Lei Lei, Qirui Yang, Qihua Cheng, Zhiqiang Xu, Yihao Liu, Huanjing Yue, Jingyu Yang, Florin-Alexandru Vasluianu, Zongwei Wu, George Ciubotariu, Radu Timofte, Zhao Zhang, Suiyi Zhao, Bo wang, Zhichao Zuo, Yanyan Wei, Kuppa Sai Sri Teja, Jayakar Reddy A, Girish Rongali, Kaushik Mitra, Zhihao Ma, Yongxu Liu, Wanying Zhang, Wei Shang, Yuhong He, Long Peng, Zhongxin Yu, Shaofei Luo, Jian Wang, Yuqi Miao, Baiang Li, Gang Wei, Rakshank Verma, Ritik Maheshwari, Rahul Tekchandani, Praful Hambarde, Satya Narayan Tazi, Santosh Kumar Vipparthi, Subrahmanyam Murala, Haopeng Zhang, Yingli Hou, Mingde Yao, Levin M S, Aniruth Sundararajan, Hari Kumar A
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
1 code implementation • 26 Mar 2024 • Yihao Liu, Jiaming Zhang, Andres Diaz-Pinto, Haowei Li, Alejandro Martin-Gomez, Amir Kheradmand, Mehran Armand
To this end, a unified platform helps push the boundary of the foundation model for medical images, facilitating the use, modification, and validation of SAM and its variants in medical image segmentation.
no code implementations • 24 Mar 2024 • Jiaming Zhang, Zhaomeng Zhang, Yihao Liu, Yaqian Chen, Amir Kheradmand, Mehran Armand
We propose a robust method to estimate the shape of linear deformable objects in realtime using scattered and unordered key points.
no code implementations • 21 Mar 2024 • Yihao Liu, Mehran Armand
The rapid development of generative technology opens up possibility for higher level of automation, and artificial intelligence (AI) embodiment in robotic systems is imminent.
1 code implementation • 13 Mar 2024 • Yihao Liu, Feng Xue, Anlong Ming
Third, to reduce the reliance on massive training data, we propose a ``divide and conquer" solution.
no code implementations • 8 Mar 2024 • Junyu Chen, Yihao Liu, Shuwen Wei, Zhangxing Bian, Aaron Carass, Yong Du
Here, we propose a novel framework to concurrently estimate both the epistemic and aleatoric segmentation uncertainties for image registration.
no code implementations • 19 Feb 2024 • Savannah P. Hays, Lianrui Zuo, Yihao Liu, Anqi Feng, Jiachen Zhuo, Jerry L. Prince, Aaron Carass
Subsequently, this estimated deformation is applied to align the paired WMn counterpart of the moving CSFn image, yielding a synthetic WMn image for the fixed CSFn image.
no code implementations • 11 Dec 2023 • Qirui Yang, Qihua Cheng, Huanjing Yue, Le Zhang, Yihao Liu, Jingyu Yang
To solve this problem, we propose a single-stage network empowered by Feature Domain Adaptation (FDA) to decouple the denoising and color mapping tasks in raw LLIE.
1 code implementation • 18 Oct 2023 • Xiangyu Chen, Zheyuan Li, Yuandong Pu, Yihao Liu, Jiantao Zhou, Yu Qiao, Chao Dong
Following this, we present the benchmark results and analyze the reasons behind the performance disparity of different models across various tasks.
no code implementations • 16 Oct 2023 • Yihao Liu, Xiangyu Chen, Xianzheng Ma, Xintao Wang, Jiantao Zhou, Yu Qiao, Chao Dong
To address this issue, we propose a universal model for general image processing that covers image restoration, image enhancement, image feature extraction tasks, etc.
2 code implementations • 8 Sep 2023 • Xiangyu Chen, Zheyuan Li, Zhengwen Zhang, Jimmy S. Ren, Yihao Liu, Jingwen He, Yu Qiao, Jiantao Zhou, Chao Dong
However, the majority of available resources are still in standard dynamic range (SDR).
no code implementations • 5 Aug 2023 • Zhangxing Bian, Shuwen Wei, Yihao Liu, Junyu Chen, Jiachen Zhuo, Fangxu Xing, Jonghye Woo, Aaron Carass, Jerry L. Prince
We introduce a novel "momenta, shooting, and correction" framework for Lagrangian motion estimation in the presence of repetitive patterns and large motion.
no code implementations • 28 Jul 2023 • Junyu Chen, Yihao Liu, Shuwen Wei, Zhangxing Bian, Shalini Subramanian, Aaron Carass, Jerry L. Prince, Yong Du
Deep learning technologies have dramatically reshaped the field of medical image registration over the past decade.
no code implementations • 27 Jun 2023 • Haowei Li, Wenqing Yan, Du Liu, Long Qian, Yuxing Yang, Yihao Liu, Zhe Zhao, Hui Ding, Guangzhi Wang
The head surface is reconstructed using depth data for spatial registration, avoiding fixing tracking targets rigidly on the patient's skull.
no code implementations • 27 Jun 2023 • Yihao Liu, Xinyu Zeng, Huanchen Zhang
Lightweight data compression is a key technique that allows column stores to exhibit superior performance for analytical queries.
no code implementations • 17 Jun 2023 • Qirui Yang, Yihao Liu, Qihua Chen, Jingyu Yang
Current methods predominantly generate HDR images from a set of bracketed exposure sRGB images.
1 code implementation • 12 Apr 2023 • Yihao Liu, Jiaming Zhang, Zhangcong She, Amir Kheradmand, Mehran Armand
To assist with the development, assessment, and application of SAM on medical images, we introduce Segment Any Medical Model (SAMM), an extension of SAM on 3D Slicer - an image processing and visualization software extensively used by the medical imaging community.
1 code implementation • CVPR 2023 • Wenteng Liang, Feng Xue, Yihao Liu, Guofeng Zhong, Anlong Ming
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.
Ranked #1 on Open World Object Detection on COCO-OOD
1 code implementation • CVPR 2023 • Haoyu Chen, Jinjin Gu, Yihao Liu, Salma Abdel Magid, Chao Dong, Qiong Wang, Hanspeter Pfister, Lei Zhu
To address this issue, we present a novel approach to enhance the generalization performance of denoising networks, known as masked training.
no code implementations • 10 Mar 2023 • Junyu Chen, Yihao Liu, Yufan He, Yong Du
In the past, optimization-based registration models have used spatially-varying regularization to account for deformation variations in different image regions.
no code implementations • 10 Mar 2023 • Junyu Chen, Yihao Liu, Yufan He, Yong Du
Transformers have recently shown promise for medical image applications, leading to an increasing interest in developing such models for medical image registration.
no code implementations • 3 Mar 2023 • Yuli Wang, Anqi Feng, Yuan Xue, Lianrui Zuo, Yihao Liu, Ari M. Blitz, Mark G. Luciano, Aaron Carass, Jerry L. Prince
Normal pressure hydrocephalus~(NPH) is a brain disorder associated with enlarged ventricles and multiple cognitive and motor symptoms.
no code implementations • 1 Feb 2023 • Lianrui Zuo, Yuan Xue, Blake E. Dewey, Yihao Liu, Jerry L. Prince, Aaron Carass
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.
1 code implementation • 18 Jan 2023 • Zhangxing Bian, Fangxu Xing, Jinglun Yu, Muhan Shao, Yihao Liu, Aaron Carass, Jiachen Zhuo, Jonghye Woo, Jerry L. Prince
We show that the method outperforms existing approaches, and also exhibits improvements in speed, robustness to tag fading, and large tongue motion.
1 code implementation • CVPR 2023 • Yihao Liu, Jingwen He, Jinjin Gu, Xiangtao Kong, Yu Qiao, Chao Dong
However, we argue that pretraining is more significant for high-cost tasks, where data acquisition is more challenging.
no code implementations • 12 Dec 2022 • Lianrui Zuo, Yihao Liu, Yuan Xue, Blake E. Dewey, Samuel W. Remedios, Savannah P. Hays, Murat Bilgel, Ellen M. Mowry, Scott D. Newsome, Peter A. Calabresi, Susan M. Resnick, Jerry L. Prince, Aaron Carass
Furthermore, HACA3 is also robust to imaging artifacts and can be trained and applied to any set of MR contrasts.
1 code implementation • 12 Dec 2022 • Yihao Liu, Junyu Chen, Shuwen Wei, Aaron Carass, Jerry Prince
For digital transformations, |J| is commonly approximated using a central difference, but this strategy can yield positive |J|'s for transformations that are clearly not diffeomorphic -- even at the voxel resolution level.
1 code implementation • 2 Oct 2022 • Haomiao Ni, Yihao Liu, Sharon X. Huang, Yuan Xue
The novel design of dual branches combines the strengths of deformation-grid-based transformation and warp-free generation for better identity preservation and robustness to occlusion in the synthesized videos.
no code implementations • 12 Jul 2022 • Mingye Xu, Yali Wang, Yihao Liu, Tong He, Yu Qiao
Inspired by prompting approaches from NLP, we creatively reinterpret point cloud generation and refinement as the prompting and predicting stages, respectively.
no code implementations • 14 May 2022 • Yihao Liu, Hengyuan Zhao, Jinjin Gu, Yu Qiao, Chao Dong
However, research on the generalization ability of Super-Resolution (SR) networks is currently absent.
no code implementations • 10 May 2022 • Wenlong Zhang, Guangyuan Shi, Yihao Liu, Chao Dong, Xiao-Ming Wu
The recently proposed practical degradation model includes a full spectrum of degradation types, but only considers complex cases that use all degradation types in the degradation process, while ignoring many important corner cases that are common in the real world.
no code implementations • 10 May 2022 • Lianrui Zuo, Yihao Liu, Yuan Xue, Shuo Han, Murat Bilgel, Susan M. Resnick, Jerry L. Prince, Aaron Carass
Disentangling anatomical and contrast information from medical images has gained attention recently, demonstrating benefits for various image analysis tasks.
1 code implementation • 5 Mar 2022 • Yihao Liu, Lianrui Zuo, Shuo Han, Yuan Xue, Jerry L. Prince, Aaron Carass
The majority of deep learning (DL) based deformable image registration methods use convolutional neural networks (CNNs) to estimate displacement fields from pairs of moving and fixed images.
1 code implementation • 9 Oct 2021 • Yihao Liu, Hengyuan Zhao, Kelvin C. K. Chan, Xintao Wang, Chen Change Loy, Yu Qiao, Chao Dong
We address this problem from a new perspective, by jointly considering colorization and temporal consistency in a unified framework.
1 code implementation • ICCV 2021 • Zhipeng Zhang, Yihao Liu, Xiao Wang, Bing Li, Weiming Hu
Siamese tracking has achieved groundbreaking performance in recent years, where the essence is the efficient matching operator cross-correlation and its variants.
1 code implementation • 1 Aug 2021 • Yihao Liu, Anran Liu, Jinjin Gu, Zhipeng Zhang, Wenhao Wu, Yu Qiao, Chao Dong
We show that a well-trained deep SR network is naturally a good descriptor of degradation information.
no code implementations • 20 Jul 2021 • Wenlong Zhang, Yihao Liu, Chao Dong, Yu Qiao
To address the problem, we propose Super-Resolution Generative Adversarial Networks with Ranker (RankSRGAN) to optimize generator in the direction of different perceptual metrics.
no code implementations • 7 Jul 2021 • Anran Liu, Yihao Liu, Jinjin Gu, Yu Qiao, Chao Dong
This paper serves as a systematic review on recent progress in blind image SR, and proposes a taxonomy to categorize existing methods into three different classes according to their ways of degradation modelling and the data used for solving the SR model.
3 code implementations • 15 Jun 2021 • Hengyuan Zhao, Wenhao Wu, Yihao Liu, Dongliang He
In this paper, we present a fast exemplar-based image colorization approach using color embeddings named Color2Embed.
1 code implementation • 27 May 2021 • Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao, Chao Dong
In this work, we propose a novel learning-based approach using a spatially dynamic encoder-decoder network, HDRUNet, to learn an end-to-end mapping for single image HDR reconstruction with denoising and dequantization.
no code implementations • 13 Apr 2021 • Yihao Liu, Jingwen He, Xiangyu Chen, Zhengwen Zhang, Hengyuan Zhao, Chao Dong, Yu Qiao
In practice, photo retouching can be accomplished by a series of image processing operations.
no code implementations • 24 Mar 2021 • Lianrui Zuo, Blake E. Dewey, Aaron Carass, Yihao Liu, Yufan He, Peter A. Calabresi, Jerry L. Prince
Accuracy and consistency are two key factors in computer-assisted magnetic resonance (MR) image analysis.
1 code implementation • ECCV 2020 • Jingwen He, Yihao Liu, Yu Qiao, Chao Dong
The base network acts like an MLP that processes each pixel independently and the condition network extracts the global features of the input image to generate a condition vector.
2 code implementations • 10 Sep 2020 • Yihao Liu, Liangbin Xie, Li Si-Yao, Wenxiu Sun, Yu Qiao, Chao Dong
In this work, we further improve the performance of QVI from three facets and propose an enhanced quadratic video interpolation (EQVI) model.
no code implementations • 18 Aug 2020 • Yuqian Zhou, Michael Kwan, Kyle Tolentino, Neil Emerton, Sehoon Lim, Tim Large, Lijiang Fu, Zhihong Pan, Baopu Li, Qirui Yang, Yihao Liu, Jigang Tang, Tao Ku, Shibin Ma, Bingnan Hu, Jiarong Wang, Densen Puthussery, Hrishikesh P. S, Melvin Kuriakose, Jiji C. V, Varun Sundar, Sumanth Hegde, Divya Kothandaraman, Kaushik Mitra, Akashdeep Jassal, Nisarg A. Shah, Sabari Nathan, Nagat Abdalla Esiad Rahel, Dafan Chen, Shichao Nie, Shuting Yin, Chengconghui Ma, Haoran Wang, Tongtong Zhao, Shanshan Zhao, Joshua Rego, Huaijin Chen, Shuai Li, Zhenhua Hu, Kin Wai Lau, Lai-Man Po, Dahai Yu, Yasar Abbas Ur Rehman, Yiqun Li, Lianping Xing
The results in the paper are state-of-the-art restoration performance of Under-Display Camera Restoration.
no code implementations • 20 Jan 2020 • Yu Dong, Yihao Liu, He Zhang, Shifeng Chen, Yu Qiao
With the proposed Fusion-discriminator which takes frequency information as additional priors, our model can generator more natural and realistic dehazed images with less color distortion and fewer artifacts.
2 code implementations • ICCV 2019 • Wenlong Zhang, Yihao Liu, Chao Dong, Yu Qiao
To address the problem, we propose Super-Resolution Generative Adversarial Networks with Ranker (RankSRGAN) to optimize generator in the direction of perceptual metrics.
Ranked #1 on Image Super-Resolution on PIRM-test
45 code implementations • 1 Sep 2018 • Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Chen Change Loy, Yu Qiao, Xiaoou Tang
To further enhance the visual quality, we thoroughly study three key components of SRGAN - network architecture, adversarial loss and perceptual loss, and improve each of them to derive an Enhanced SRGAN (ESRGAN).
Ranked #2 on Face Hallucination on FFHQ 512 x 512 - 16x upscaling