no code implementations • CVPR 2025 • JunMing Hou, Xiaoyu Chen, Ran Ran, Xiaofeng Cong, Xinyang Liu, Jian Wei You, Liang-Jian Deng
Building on this insight, we propose a novel binary pan-sharpening network, termed BNNPan, structured around the Prior-Integrated Binary Frequency (PIBF) module that features three key ingredients: Binary Wavelet Transform Convolution, Latent Diffusion Prior Compensation, and Channel-wise Distribution Calibration.
no code implementations • 20 Dec 2024 • Chuanrui Hu, Shichong Xie, Baoxin Wang, Bin Chen, Xiaofeng Cong, Jun Zhang
To address these issues, we propose a general-purpose and training-free web search agent by level-aware navigation, Level-Navi Agent, accompanied by a well-annotated dataset (Web24) and a suitable evaluation metric.
1 code implementation • 29 Sep 2024 • Xiaofeng Cong, Jing Zhang, Yeying Jin, JunMing Hou, Yu Zhao, Jie Gui, James Tin-Yau Kwok, Yuan Yan Tang
ColorCode offers three key features: 1) color enhancement, producing an enhanced image with a fixed color; 2) color adaptation, enabling controllable adjustments of long-wavelength color components using guidance images; and 3) color interpolation, allowing for the smooth generation of multiple colors through continuous sampling of the color code.
no code implementations • 10 Sep 2024 • Siyu Zhai, Zhibo He, Xiaofeng Cong, JunMing Hou, Jie Gui, Jian Wei You, Xin Gong, James Tin-Yau Kwok, Yuan Yan Tang
In this paper, we propose a general adversarial attack protocol.
no code implementations • 30 May 2024 • Xiaofeng Cong, Yu Zhao, Jie Gui, JunMing Hou, DaCheng Tao
Underwater image enhancement (UIE) presents a significant challenge within computer vision research.
1 code implementation • 22 Apr 2024 • Yu-Xin Zhang, Jie Gui, Baosheng Yu, Xiaofeng Cong, Xin Gong, Wenbing Tao, DaCheng Tao
For supervised DL-PCR methods, we organize the discussion based on key aspects, including the registration procedure, optimization strategy, learning paradigm, network enhancement, and integration with traditional methods; For unsupervised DL-PCR methods, we classify them into correspondence-based and correspondence-free approaches, depending on whether they require explicit identification of point-to-point correspondences.
1 code implementation • 19 Apr 2024 • JunMing Hou, ZiHan Cao, Naishan Zheng, Xuan Li, Xiaoyu Chen, Xinyang Liu, Xiaofeng Cong, Man Zhou, Danfeng Hong
In this way, our proposed method is capable of benefiting the cascaded modeling rule while achieving favorable performance in the efficient manner.
1 code implementation • CVPR 2024 • Xiaofeng Cong, Jie Gui, Jing Zhang, JunMing Hou, Hao Shen
There are two distinctions between nighttime and daytime haze.
1 code implementation • 9 Jun 2023 • Jie Gui, Xiaofeng Cong, Lei He, Yuan Yan Tang, James Tin-Yau Kwok
On the one hand, the dehazing task is an illposedness problem, which means that no unique solution exists.
1 code implementation • 30 Mar 2023 • Jie Gui, Xiaofeng Cong, Chengwei Peng, Yuan Yan Tang, James Tin-Yau Kwok
In this paper, we focus on designing a group of attack methods based on first order gradient to verify the robustness of the existing dehazing algorithms.
1 code implementation • 7 Jun 2021 • Jie Gui, Xiaofeng Cong, Yuan Cao, Wenqi Ren, Jun Zhang, Jing Zhang, Jiuxin Cao, DaCheng Tao
With the development of convolutional neural networks, hundreds of deep learning based dehazing methods have been proposed.
no code implementations • 25 Sep 2020 • Pengxu Wei, Hannan Lu, Radu Timofte, Liang Lin, WangMeng Zuo, Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Gang Zhang, Jingtuo Liu, Junyu Han, Errui Ding, Tangxin Xie, Liang Cao, Yan Zou, Yi Shen, Jialiang Zhang, Yu Jia, Kaihua Cheng, Chenhuan Wu, Yue Lin, Cen Liu, Yunbo Peng, Xueyi Zou, Zhipeng Luo, Yuehan Yao, Zhenyu Xu, Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Tongtong Zhao, Shanshan Zhao, Yoseob Han, Byung-Hoon Kim, JaeHyun Baek, HaoNing Wu, Dejia Xu, Bo Zhou, Wei Guan, Xiaobo Li, Chen Ye, Hao Li, Yukai Shi, Zhijing Yang, Xiaojun Yang, Haoyu Zhong, Xin Li, Xin Jin, Yaojun Wu, Yingxue Pang, Sen Liu, Zhi-Song Liu, Li-Wen Wang, Chu-Tak Li, Marie-Paule Cani, Wan-Chi Siu, Yuanbo Zhou, Rao Muhammad Umer, Christian Micheloni, Xiaofeng Cong, Rajat Gupta, Keon-Hee Ahn, Jun-Hyuk Kim, Jun-Ho Choi, Jong-Seok Lee, Feras Almasri, Thomas Vandamme, Olivier Debeir
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020.