Zhenjun Tang

Guangxi Normal University · School of Computer Science and Engineering

Reversible Data Hiding in Encrypted Images (RDHEI) has attracted considerable attention, as it can facilitate the management of massive encrypted images and can be employed for covert communication. Recent research has demonstrated that RDHEI methods with pixel prediction can achieve a more significant embedding capacity than those that do not util...

Copy detection is a key task of image copyright protection. Most robust hashing schemes do not make satisfied performance of image copy detection yet. To address this, a robust hashing scheme with deep features and Meixner moments is proposed for image copy detection. In the proposed hashing, global deep features are extracted by applying tensor Si...

Reversible data hiding (RDH) in encrypted images has emerged as an effective technique for securely storing and managing confidential images in the cloud. However, most RDH methods in shared images (RDHSI) are designed for uncompressed images and cannot be applied for JPEG images. To address this issue, we propose a novel RDH in shared JPEG images....

Image hashing is an efficient technique of image processing for various applications, such as retrieval, copy detection and authentication. In this paper, we design a novel image hashing algorithm using LRSMD (low-rank sparse matrix decomposition). Firstly, an input image is preprocessed by interpolation, Gaussian blur and color space conversion. N...

Copy detection is a key task of image copyright protection. This paper proposes a robust image hashing algorithm by CP decomposition and discrete cosine transform (DCT) for copy detection. The first contribution is the third-order tensor construction with low-frequency coefficients in the DCT domain. Since the low-frequency DCT coefficients contain...

Image hashing is a useful technique of many multimedia systems, such as image authentication, image copy detection, tampering detection and image quality assessment (IQA). However, most image hashing schemes do not make desirable performance of IQA. To tackle this, a new hashing scheme with deep and texture features is proposed for reduced-referenc...

Reversible data hiding in encrypted images (RDHEI) is an effective technology of protecting private data. In this paper, a high-capacity RDHEI method with asymmetric coding and bit-plane block compression is proposed. Our major contributions are twofold. (1) We propose an asymmetric coding technique for processing prediction error (PE) blocks befor...

Hashing is an efficient technology for various image tasks. This paper proposes an effective image hashing with deep and moment features for content authentication. The deep features are calculated by Wavelet Scattering Network (ScatNet) and local tangent space alignment (LTSA). The ScatNet is used to construct a third-order tensor from the image b...

Image hiding aims to hide the secret data in the cover image for secure transmission. Recently, with the development of deep learning, some deep learning-based image hiding methods were proposed. However, most of them do not achieve outstanding hiding performance yet. To address this issue, we propose a new image hiding framework called CAE-NF, whi...

This paper proposes a novel video hashing with tensor robust Principal Component Analysis (PCA) and Histogram of Optical Flow (HOF) for copy detection. In the proposed hashing, a video is divided into some video groups. For each video group, a low-rank secondary frame is constructed from the low-rank component decomposed by applying tensor robust P...

No-reference (NR) image quality assessment (IQA) is an important task of computer vision. Most NR-IQA methods via deep neural networks do not reach desirable IQA performance and have bulky models which make them difficult to be used in the practical scenarios. This paper proposes a lightweight transformer and multi-head prediction network for NR-IQ...

Reversible data hiding in encrypted images (RDHEI) is an essential data security technique. Most RDHEI methods cannot perform well in embedding capacity and security. To address this issue, we propose a new RDHEI method using Chinese remainder theorem-based secret sharing (CRTSS) and hybrid coding. Specifically, a hybrid coding is first proposed fo...

Multi-view clustering has gained great progress recently, which employs the representations from different views for improving the final performance. In this paper, we focus on the problem of multi-view clustering based on the Markov chain by considering low-rank constraints. Since most existing methods fail to simultaneously characterize the relat...

Robust hashing is a powerful technique for processing large-scale images. Currently, many reported image hashing schemes do not perform well in balancing the performances of discrimination and robustness and thus they cannot efficiently detect image copies, especially the image copies with multiple distortions. To address this, we exploit global an...

Image Quality Assessment (IQA) is a critical task of computer vision. Most Full-Reference (FR) IQA methods have limitation in the accurate prediction of perceptual qualities of the traditional distorted images and the Generative Adversarial Networks (GAN) based distorted images. To address this issue, we propose a novel method by Unifying Dual-Atte...

This paper proposes a lightweight image hashing based on knowledge distillation and optimal transport for face retrieval. A key contribution is the attention-based triplet knowledge distillation, whose loss function includes attention loss, Kullback-Leibler (KL) loss and identity loss. It can significantly reduce network size with almost no decreas...

Reversible data hiding in encrypted images (RDHEI) is a useful technique for protecting data security, but most RDHEI methods do not make a satisfied embedding performance yet. To address this, we propose a novel RDHEI method via arranging blocks of bit-planes to vacate more room. In the proposed RDHEI method, the eight bit-planes of prediction err...

Image–text matching is a crucial branch in multimedia retrieval which relies on learning inter-modal correspondences. Most existing methods focus on global or local correspondence and fail to explore fine-grained global–local alignment. Moreover, the issue of how to infer more accurate similarity scores remains unresolved. In this study, we propose...

Digital images are easily corrupted during transmission. Most image denoising methods cannot perform well on restoring the secret image extracted from a corrupted stego image. To deal with this issue, we propose a new secret image restoration method with convex hull and elite opposition-based learning strategy. Specifically, the pixel distortion va...

Robust hashing is a useful technique for the image applications of watermarking, authentication, quality assessment and copy detection. This paper proposes a new robust hashing for image copy detection by using local tangent space alignment (LTSA). A key contribution is the weighted visual map computation based on the difference of Gaussian (DOG) a...

In the tracking literature, foreground and background information have been extensively investigated to discriminate a target from its surrounding background. However, both foreground and background possess their own spatial-temporal correlation relationship that provide significant information to separate the target from its surrounding background...

Image quality assessment (IQA) is an important task of image processing and has diverse applications, such as image super-resolution reconstruction, image transmission and monitoring systems. This paper proposes a perceptual hashing algorithm with complementary color wavelet transform (CCWT) and compressed sensing (CS) for reduced-reference (RR) IQ...

The inability to fully exploit domain-specific knowledge and the lack of an effective integration method have been the difficulties and focus of multimodal sentiment analysis. In this paper, we propose heterogeneous graph convolution with in-domain self-supervised multi-task learning for multimodal sentiment analysis (HIS-MSA) to solve these proble...

Research of visual neural networks (VNNs) is one of the most important topics in deep learning and has received wide attention from industry and academia for their promising performance. The applications of VNNs range from image classification and target detection to scene segmentation in various fields such as transportation, healthcare and financ...

Image captioning is a challenging task, i.e., given an image machine automatically generates natural language that matches its semantic content and has attracted much attention in recent years. However, most existing models are designed manually, and their performance depends heavily on the expert experience of the designer. In addition, the comput...

The similarity calculation is too simple in most cross-modal hash retrieval methods, which do not consider the impact of the relations between instances. To solve this problem, this paper proposes a reasoning method based on multiple instance relation graphs. By constructing similarity matrices, we establish global and local instance relation graph...

Occlusion is known as one of the most challenge factors in long-term tracking for its unpredictable shape. Existing works devoted into the design of loss functions, training strategies or model architectures, which are considered to have not directly touched the key point. Alternatively, we come up a direct and natural idea that is discarding thing...

Variation of scales or aspect ratios has been one of the main challenges for tracking. To overcome this challenge, most existing methods adopt either multi-scale search or anchor-based schemes, which use a predefined search space in a handcrafted way and therefore limit their performance in complicated scenes. To address this problem, recent anchor...

Hashing scheme is a high‐efficiency technique for processing massive images. Two critical metrics of the hashing scheme are discrimination and robustness, but most schemes do not get satisfied classification performance between them. This paper proposes a novel hashing scheme via image feature map and 2D PCA. First, the proposed scheme extracts loc...

Image hashing is an effective technology for extensive image applications, such as retrieval, authentication and copy detection. This paper designs a new image hashing scheme based on saliency map and sparse model. The major contributions are twofold. The first contribution is the construction of a weighted image representation by combining a visua...

Reversible data hiding (RDH) is an important topic of data hiding. In this paper, we exploit pixel-based pixel value ordering prediction (PPVO) and pairwise prediction-error expansion (PEE) to design a novel RDH with pairwise PEE and 2-dimensional prediction-error histogram (2D-PEH) decomposition. Specifically, for each pair of pixels, they are acc...

Despite that both local and context information are crucial for robust tracking, existing CNN-based and transformer-based methods mainly focus on one of these aspects. Consequently, the former fails to exploit rich global context information due to the limited receptive field, while the latter suffers from the deficiencies in constructing the local...

Robust tracking has a variety of practical applications. Despite many years of progress, it is still a difficult problem due to enormous uncertainties in real-world scenes. To address this issue, we propose a robust anchor-free based tracking model with uncertainty estimation. Within the model, a new data-driven uncertainty estimation strategy is p...

Compression technology for representing image is on demand for efficiently processing images in the big data era. Image hashing is an effective compression technology for computing a short representation based on visual content of input image. Currently, most reported image hashing algorithms have weakness in making a desirable classification betwe...

Perceptual image hashing is an effective and efficient way to identify images in large-scale databases, where two major performances are robustness and discrimination. A better tradeoff between robustness and discrimination is still a severe challenge for the current hashing research. Aiming at this issue, we design a novel perceptual image Hashing...

Image copy detection is an important technology of copyright protection. This paper proposes an efficient hashing method for image copy detection using 2D-2D (two-directional two-dimensional) PCA (Principal Component Analysis). The key is the discovery of the translation invariance of 2D-2D PCA. With the property of translation invariance, a novel...

Existing algorithms of dish recognition mainly focus on accuracy with predefined classes, thus limiting their application scope. In this paper, we propose a practical two-stage dish recognition framework (DRNet) that yields a tradeoff between speed and accuracy while adapting to the variation in class numbers. In the first stage, we build an arbitr...

Digital images are easily corrupted by attacks during transmission and most data hiding methods have limitations in resisting cropping and noise attacks. Aiming at this problem, we propose a robust image data hiding method based on multiple backups and pixel bit weight (PBW). Especially multiple backups of every pixel bit are pre-embedded into a co...

Video hashing is a useful technology for diverse video applications, such as digital water-marking, copy detection and content authentication. This paper proposes a novel efficient video hashing based on low-rank frames. A key contribution is the low-rank frame calculation using the low-rank approximation of singular value decomposition (SVD). As t...

Vacating room after encryption (VRAE) is a popular framework of reversible data hiding for encrypted images (RDHEI). Most VRAE based RDHEI methods do not make a desirable payload. To address this issue, this paper proposes a novel data hiding technique using adaptive difference recovery (ADR) and exploits this novel technique to design an efficient...

Video hashing is a useful technique of many multimedia systems, such as video copy detection, video authentication, tampering localization, video retrieval, and anti-privacy search. In this paper, we propose a novel video hashing with secondary frames and invariant moments. An important contribution is the secondary frame construction with 3D discr...

Image hashing is a useful technology of many multimedia systems, such as image retrieval, image copy detection, multimedia forensics and image authentication. Most of the existing hashing algorithms do not reach a good classification between robustness and discrimination and some hashing algorithms based on dimensionality reduction have high comput...

Abstract Reversible data hiding (RDH) is a useful technique of data security. Embedding capacity is one of the most important performance of RDH for encrypted image. Many existing RDH algorithms for encrypted image do not reach desirable embedding capacity yet. To address this problem, a new RDH algorithm is proposed for encrypted image based on ad...

Multimedia hashing is a useful technology of multimedia management, e.g., multimedia search and multimedia security. This paper proposes a robust multimedia hashing for processing videos. The proposed video hashing constructs a high-dimensional matrix via gradient features in the discrete wavelet transform (DWT) domain of preprocessed video, learns...

A practical long-term tracker typically contains three key properties, i.e. an efficient model design, an effective global re-detection strategy and a robust distractor awareness mechanism. However, most state-of-the-art long-term trackers (e.g., Pseudo and re-detecting based ones) do not take all three key properties into account and therefore may...

Despite the great success of Siamese-based trackers, their performance under complicated scenarios is still not satisfying, especially when there are distractors. To this end, we propose a novel Siamese relation network, which introduces two efficient modules, i.e. Relation Detector (RD) and Refinement Module (RM). RD performs in a meta-learning wa...

Reversible data hiding in encrypted images (RD-HEI) is an effective technique of data security. Most state-of-the-art RDHEI methods do not achieve desirable payload yet. To address this problem, we propose a new RDHEI method with hierarchical embedding. Our contributions are twofold. (1) A novel technique of hierarchical label map generation is pro...

Because of the widespread popularity of JPEG image compression format, reversible data hiding (RDH) for JPEG images has practical application value with increasing research attention. This paper proposes a dual-image RDH method based on a modification of the discrete cosine transform (DCT) coefficients. Because of the limited embedding capacity, a...

Most data hiding methods have limitations in resisting cropping and noise attacks. Aiming at this problem, a robust data hiding with multiple backups and optimized reference matrix is proposed in this paper. Specifically, secret data is divided into a set of groups and multiple backups of each group data are generated according to the number of bac...

In order to protect the intellectual property of neural network, an owner may select a set of trigger samples and their corresponding labels to train a network, and prove the ownership by the trigger set without revealing the inner mechanism and parameters of the network. However, if an attacker is allowed to access the neural network, he can forge...

Image hashing has attracted much attention of the community of multimedia security in the past years. It has been successfully used in social event detection, image authentication, copy detection, image quality assessment, and so on. This paper presents a novel image hashing with low-rank representation (LRR) and ring partition. The proposed hashin...

Video hashing is a novel technique of multimedia processing and finds applications in video retrieval, video copy detection, anti-piracy search and video authentication. In this paper, we propose a robust video hashing based on discrete cosine transform (DCT) and non-negative matrix decomposition (NMF). The proposed video hashing extracts secure fe...

Abstract Image hashing is an efficient technology for processing digital images and has been successfully used in image copy detection, image retrieval, image authentication, image quality assessment, and so on. In this paper, we design a new image hashing with compressed sensing (CS) and ordinal measures. This hashing method uses a visual attentio...

Stego-images are often contaminated by interchannel noise or active noise attack when communicating on the Web. And it is challenging to restore embedded image from corrupted stego-image. This paper studies a kNN-bit approximation algorithm to remove noises in embedded image. The proposed algorithm distinguishes reliable bits from extracted bits, a...

Dual-image reversible data hiding (RDH) technology has been an active research area and became an essential part of information security because of its unique advantages in security, embedding capacity and visual quality. For a dual-image RDH strategy, message data is embedded into a cover image to generate two marked images with similar visual qua...

In this paper, a reversible data hiding method in encrypted image (RDHEI) is proposed. Prior to image encryption, the embeddable pixels are selected from an original image according to prediction errors due to adjacent pixels with strong correlation. Then the embeddable pixels and the other pixels are both rearranged and encrypted to generate an en...

Image hashing is an efficient technique of multimedia processing for many applications, such as image copy detection, image authentication, and social event detection. In this study, the authors propose a novel image hashing with visual attention model and invariant moments. An important contribution is the weighted DWT (discrete wavelet transform)...

Reversible image authentication (RIA) is an emerging research field for image tampering operation detection. Tampered regions can be localized precisely by embedding an authentication code (AC) into each divided image block in advance. Once the image is identified as an authentic image, the original image can be recovered without any loss. Under th...

Reversible data hiding (RDH) in color image is an important topic of data hiding. This paper presents an efficient RDH algorithm for color image via double-layer embedding. The key contribution is the proposed double-layer embedding technique based on histogram shifting (HS). This technique exploits image interpolation to generate prediction error...

A new scheme of reversible data hiding in encrypted images is proposed in this paper. Content owner first encrypts divided blocks by the specific stream cipher and permutation. During data embedding, data hider embeds secret data into the compressed least significant bits (LSB) and the most significant bits (MSB) of a part of pixels in the smooth r...

With the availability of highly sophisticated editing tools, the authenticity of digital images has now become questionable. The level of image tampering is getting higher and higher, and the tampering procedures become more and more complicated. To recognize the tampering area of the original image, the tampered image is usually executed a series...