Search Results for author: Zhili Zhou

Found 7 papers, 0 papers with code

ContextBLIP: Doubly Contextual Alignment for Contrastive Image Retrieval from Linguistically Complex Descriptions

no code implementations29 May 2024 Honglin Lin, Siyu Li, Guoshun Nan, Chaoyue Tang, Xueting Wang, Jingxin Xu, Rong Yankai, Zhili Zhou, Yutong Gao, Qimei Cui, Xiaofeng Tao

The main challenges lie in aligning key contextual cues in two modalities, where these subtle cues are concealed in tiny areas of multiple contrastive images and within the complex linguistics of textual descriptions.

Image Retrieval Retrieval

GanFinger: GAN-Based Fingerprint Generation for Deep Neural Network Ownership Verification

no code implementations25 Dec 2023 Huali Ren, Anli Yan, Xiaojun Ren, Pei-Gen Ye, Chong-zhi Gao, Zhili Zhou, Jin Li

To address these issues, we propose a network fingerprinting approach, named as GanFinger, to construct the network fingerprints based on the network behavior, which is characterized by network outputs of pairs of original examples and conferrable adversarial examples.

Traceable and Authenticable Image Tagging for Fake News Detection

no code implementations20 Nov 2022 Ruohan Meng, Zhili Zhou, Qi Cui, Kwok-Yan Lam, Alex Kot

Extensive experiments, on diverse datasets and unseen manipulations, demonstrate that the proposed tagging approach achieves excellent performance in the aspects of both authenticity verification and source tracing for reliable fake news detection and outperforms the prior works.

Fake News Detection TAG

Auto-Focus Contrastive Learning for Image Manipulation Detection

no code implementations20 Nov 2022 Wenyan Pan, Zhili Zhou, Guangcan Liu, Teng Huang, Hongyang Yan, Q. M. Jonathan Wu

However, we argue that those models achieve sub-optimal detection performance as it tends to: 1) distinguish the manipulation traces from a lot of noisy information within the entire image, and 2) ignore the trace relations among the pixels of each manipulated region and its surroundings.

Contrastive Learning Image Manipulation +1

Real-World Image Super Resolution via Unsupervised Bi-directional Cycle Domain Transfer Learning based Generative Adversarial Network

no code implementations19 Nov 2022 Xiang Wang, Yimin Yang, Zhichang Guo, Zhili Zhou, Yu Liu, Qixiang Pang, Shan Du

First, the UBCDTN is able to produce an approximated real-like LR image through transferring the LR image from an artificially degraded domain to the real-world LR image domain.

Generative Adversarial Network Image Super-Resolution +1

Continual Learning for Steganalysis

no code implementations3 Sep 2022 Zihao Yin, Ruohan Meng, Zhili Zhou

To detect the existing steganographic algorithms, recent steganalysis methods usually train a Convolutional Neural Network (CNN) model on the dataset consisting of corresponding paired cover/stego-images.

Continual Learning Steganalysis

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