no code implementations • COLING 2022 • Weidong Tian, Haodong Li, Zhong-Qiu Zhao
The attention mechanism can highlight fine-grained features with critical information, thus ensuring that feature extraction emphasizes the objects related to the questions.
no code implementations • 1 Jan 2024 • Haodong Li, Gelei Deng, Yi Liu, Kailong Wang, Yuekang Li, Tianwei Zhang, Yang Liu, Guoai Xu, Guosheng Xu, Haoyu Wang
In this paper, we introduce a detailed framework designed to detect and assess the presence of content from potentially copyrighted books within the training datasets of LLMs.
1 code implementation • 19 Nov 2023 • Yixun Liang, Xin Yang, Jiantao Lin, Haodong Li, Xiaogang Xu, Yingcong Chen
The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for creating imaginative 3D assets across various real-world scenarios.
1 code implementation • 8 Nov 2022 • Peiyu Zhuang, Haodong Li, Rui Yang, Jiwu Huang
The ReLoc framework mainly consists of an image restoration module and a tampering localization module.
no code implementations • 11 Aug 2022 • Chenlong Zhang, Dawei Li, Haodong Li
Fixed-wing Miniature Air Vehicle (MAV) is not only coupled with longitudinal motion, but also more susceptible to wind disturbance due to its lighter weight, which brings more challenges to its altitude and airspeed controller design.
1 code implementation • ICCV 2019 • Haodong Li, Jiwu Huang
The proposed method employs a fully convolutional network that is based on high-pass filtered image residuals.
1 code implementation • 22 Aug 2018 • Haodong Li, Bin Li, Shunquan Tan, Jiwu Huang
In this paper, we address the problem of detecting deep network generated (DNG) images by analyzing the disparities in color components between real scene images and DNG images.
Multimedia
no code implementations • 9 Sep 2017 • Bolin Chen, Haodong Li, Weiqi Luo
The extensive results show that the proposed method can outperform the currently best method based on hand crafted features and three related methods based on CNN for image steganalysis and/or forensics, achieving the state-of-the-art results.