Search Results for author: Xiaofeng Cong

Found 12 papers, 7 papers with code

Binarized Neural Network for Multi-spectral Image Fusion

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.

Binarization

Level-Navi Agent: A Framework and benchmark for Chinese Web Search Agents

no code implementations20 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.

Underwater Organism Color Enhancement via Color Code Decomposition, Adaptation and Interpolation

1 code implementation29 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.

Image Enhancement

A Comprehensive Survey on Underwater Image Enhancement Based on Deep Learning

no code implementations30 May 2024 Xiaofeng Cong, Yu Zhao, Jie Gui, JunMing Hou, DaCheng Tao

Underwater image enhancement (UIE) presents a significant challenge within computer vision research.

Disentanglement UIE

Deep Learning-Based Point Cloud Registration: A Comprehensive Survey and Taxonomy

1 code implementation22 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.

Autonomous Driving Deep Learning +1

Linearly-evolved Transformer for Pan-sharpening

1 code implementation19 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.

Fooling the Image Dehazing Models by First Order Gradient

1 code implementation30 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.

Adversarial Attack Image Dehazing +1

A Comprehensive Survey and Taxonomy on Single Image Dehazing Based on Deep Learning

1 code implementation7 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.

Image Dehazing Single Image Dehazing

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