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Claim this profileWorks307 from public data
- Activating More Pixels in Image Super-Resolution Transformer1,170
A novel Hybrid Attention Transformer (HAT) is proposed, which combines both channel attention and window-based self-attention schemes, thus making use of their complementary advantages of being able to utilize global statistics and strong local fitting capability.
- User's Guide for CFSQP Version 2.0: A C Code for Solving (Large Scale) Constrained Nonlinear (Minimax) Optimization Problems, Generating Iterates Satisfying All Inequality Constraints384
CFSQP is an implementation of two algorithms based on Sequential Quadratic Programming (SQP), modi ed so as to generate feasible iterates and the merit function used in both searches is the maximum of the objective functions if there is no non linear equality constraints, or an exact penalty function if nonlinear equality constraints are present.
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- Stochastic memristive devices for computing and neuromorphic applications307
This work demonstrates memristor-based stochastic bitstreams in both time and space domains, and shows that an array of binary memristors can act as a multi-level "analog" device for neuromorphic applications.
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- SmartEdit: Exploring Complex Instruction-Based Image Editing with Multimodal Large Language Models213
A Bidirectional Interaction Module (BIM) is proposed that enables comprehensive bidirectional information interactions between the input image and the MLLM output and demonstrates that a small amount of complex instruction editing data can effectively stimulate SmartEdit’ s editing capabilities for more complex instructions.
- A Review of Compressive Sensing in Information Security Field189
This paper reviews CS in information security field from two aspects: theoretical security and application security, and indicates some other possible application research topics in future.
- HAT: Hybrid Attention Transformer for Image Restoration179
A new Hybrid Attention Transformer (HAT) is proposed that combines both channel attention and window-based self-attention schemes, thus making use of their complementary advantages, and achieves state-of-the-art performance both quantitatively and qualitatively.
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- Tag-assisted Multimodal Sentiment Analysis under Uncertain Missing Modalities126
A Tag-Assisted Transformer Encoder (TATE) network is proposed to handle the problem of missing uncertain modalities, and a tag encoding module is designed to cover both the single modality and multiple modalities missing cases.
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- A Benchmark for Sparse Coding: When Group Sparsity Meets Rank Minimization119
An adaptive dictionary is designed to bridge the gap between group-based sparse coding (GSC) and rank minimization, and WSNM is found to be the closest one to the real singular values of each patch group and is translated into a non-convex weighted norm minimization problem in GSC.
- From Rank Estimation to Rank Approximation: Rank Residual Constraint for Image Restoration116
Experimental results demonstrate that the proposed RRC method outperforms many state-of-the-art schemes in both the objective and perceptual quality.
- Embedding cryptographic features in compressive sensing114
It is demonstrated that random permutation is an acceptable permutation with overwhelming probability, which can effectively relax the Restricted Isometry Constant for parallel compressive sensing and is utilized to design a secure parallel compression sensing scheme.
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- Cross-Receptive Focused Inference Network for Lightweight Image Super-Resolution91
A novel Cross-receptive Field Guided Transformer is designed to enable the selection of contextual information required for reconstruction by using a modulated convolutional kernel that understands the current semantic information and exploits the information interaction within different self-attention.
- Bi-level Protected Compressive Sampling89
This paper proposes a bi-level protected CS (BLP-CS) model which makes use of the advantage of measurement matrix construction without restricted isometry property (RIP), and demonstrates that the new model can be applied in circumstances where the measurement matrix can be reused.
- Perceptual Quality Assessment of Low-light Image Enhancement88
This article proposes a new FR low-light image enhancement quality assessment (LIEQA) index by evaluating the image quality from four aspects: luminance enhancement, color rendition, noise evaluation, and structure preserving, which have captured the most key aspects of low-lights enhancement.
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- Detecting Adversarial Examples from Sensitivity Inconsistency of Spatial-Transform Domain82
This work reveals that normal examples are insensitive to the fluctuations occurring at the highly-curved region of the decision boundary, while AEs typically designed over one single domain exhibit exorbitant sensitivity on such fluctuations, and designs another classifier with transformed decision boundary to detect AEs.
- A Survey of Orthogonal Moments for Image Representation: Theory, Implementation, and Evaluation82
A comprehensive survey of the orthogonal moments for image representation, covering recent advances in fast/accurate calculation, robustness/invariance optimization, definition extension, and application.
- SMDS-Net: Model Guided Spectral-Spatial Network for Hyperspectral Image Denoising80
A novel model-guided interpretable network for HSI denoising to tackle the problem of spatial redundancy, spectral low-rankness, and spectral-spatial correlations of HSIs and establishes a subspace-based multidimensional sparse (SMDS) model under the umbrella of tensor notation.
- Deep Generative Model for Image Inpainting With Local Binary Pattern Learning and Spatial Attention74
This work proposes a new end-to-end, two-stage (coarse- to-fine) generative model through combining a local binary pattern (LBP) learning network with an actual inpainting network, designed to accurately predict the structural information of the missing region.
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- Improved known-plaintext attack to permutation-only multimedia ciphers73
With a new concept of composite representation, the underlying theoretical rules governing the KPA attack on a permutation-only cipher are revealed, and some attractive algorithms outperforming the state-of-the-art methods in terms of computational complexity are developed.
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- DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models67
Equipped with the DeSRA, the cause and characteristics of the GAN artifacts produced in unseen test data without ground-truths are analyzed and artifacts from inference are eliminated and the ability of SR models to be applied in real-world scenarios is improved.
- In Situ Nanoscale Electric Field Control of Magnetism by Nanoionics65
Direct, nonvolatile, and reversible control of nanomagnetism in solid-state ferromagnetic thin films is achieved by controlling the chemical composition of the film through field-driven ion redistribution.
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- Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision60
A temporal pyramid network for pedestrian trajectory prediction through a squeeze modulation and a dilation modulation is proposed and a coarse-to-fine fusion strategy with multi-supervision is proposed that can fully exploit both the long-range and short-range information of the trajectory.
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- Mitigating Inconsistencies in Multimodal Sentiment Analysis under Uncertain Missing Modalities58
An Ensemble-based Missing Modality Reconstruction (EMMR) network is proposed to detect and recover semantic features of the key missing modality and check the semantic consistency to determine whether the absent modality is crucial to the overall sentiment polarity.
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- Privacy-Preserving distributed deep learning based on secret sharing53
This work designs a privacy-preserving DDL framework such that all the participants can keep their local datasets private with low communication and computational cost, while still maintaining the accuracy and efficiency of the learned model.
- Conduction mechanism of a TaO x -based selector and its application in crossbar memory arrays53
The integrated selector device showed a reliable resistive switching behavior with a high non-linearity in the low resistance state (LRS), which can effectively mitigate the sneak path current issue in RRAM crossbar arrays.
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- NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results45
This paper reviews the challenge on constrained high dynamic range (HDR) imaging that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2022, and the competition set-up, datasets, proposed methods and their results.
- Unifying Image Processing as Visual Prompting Question Answering44
Inspired by NLP question answering techniques, PromptGIP treats the input-output image pair as a structured question-answer sentence, thereby reprogramming the image processing task as a prompting QA problem, eliminating the need for task-specific finetuning.
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- Toward Visual Behavior and Attention Understanding for Augmented 360 Degree Videos43
To bridge the gap between the saliency prediction on real-world scenes and on scenes augmented by virtual information, the ARVR saliency dataset is constructed and a model that is capable of solving theSaliency prediction problem in AR is designed.
- Noise Level Estimation for Natural Images Based on Scale-Invariant Kurtosis and Piecewise Stationarity43
A novel noise level estimation approach for natural images is proposed by jointly exploiting the piecewise stationarity and a regular property of the kurtosis in bandpass domains by adapting a K-means-based algorithm to adaptively partition an image into a series of non-overlapping regions.
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- STGlow: A Flow-Based Generative Framework With Dual-Graphormer for Pedestrian Trajectory Prediction37
This article proposes a novel generative flow-based framework with a dual-graphormer combined with the graph structure to more adequately model the temporal dependencies and the mutual spatial interactions for pedestrian trajectory prediction (STGlow).
- Image Copy-Move Forgery Detection via Deep PatchMatch and Pairwise Ranking Learning36
A novel end-to-end CMFD framework that integrates the strengths of conventional and deep learning methods and utilizes features extracted from high-resolution scales to seek explicit and reliable point-to-point matching between source and target regions.
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- Processing-Aware Privacy-Preserving Photo Sharing over Online Social Networks34
This work addresses the problem of designing privacy-preserving, high-fidelity, storage-efficient photo sharing solution over Facebook and suggests a DCT-domain image encryption scheme that is robust against these lossy operations.
- Computation Outsourcing Meets Lossy Channel: Secure Sparse Robustness Decoding Service in Multi-Clouds33
Experimental results show that the encryption algorithm improves compressibility and reconstruction performance compared with the case of no encryption, and the proposed privacy-assured outsourcing of SRDS is highly robust and efficient.
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- Robust Privacy-Preserving Image Sharing over Online Social Networks (OSNs)32
This article considers the problem of designing a secure, robust, high-fidelity, storage-efficient image-sharing scheme over Facebook, a representative OSN that is widely accessed and proposes a DCT-domain image encryption/decryption framework that is robust against these lossy operations.
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- A Block Compressive Sensing Based Scalable Encryption Framework for Protecting Significant Image Regions31
The existing Block Compressive Sensing (BCS) based image ciphers adopted the same sampling rate for all the blocks, which may lead to the desirable result that after subsampling, significant blocks lose some more-useful information while insignificant blocks still retain some less- useful information.
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- Learning a Deep Agent to Predict Head Movement in 360-Degree Images28
This article proposes a model to predict the trajectory of head movement and stipulates that the model imitates the behaviors of human demonstrators, to ensure the accurate simulation of visual behaviors during the watching of panoramas.
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- Learning A Low-Level Vision Generalist via Visual Task Prompt24
A Visual task Prompt-based Image Processing (VPIP) framework is proposed, which employs visual task prompts to manage tasks with different input-target domains and allows flexible selection of backbone network suitable for general tasks.
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- The Power Of Triply Complementary Priors For Image Compressive Sensing16
A joint low-rank and deep (LRD) image model, which contains a pair of triply complementary priors, namely external and internal, deep and shallow, and local and nonlocal priors is proposed, which is a novel hybrid plug-and-play (H-PnP) framework based on the LRD model for image CS.
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- Joint Patch-Group Based Sparse Representation for Image Inpainting10
Compared with existing sparse representation models, the proposed JPG-SR provides a powerful mechanism to integrate the local sparsity and nonlocal self-similarity of images and outperforms several state-of-the-art methods in both objective and perceptual quality.
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- Towards Efficient SDRTV-to-HDRTV by Learning From Image Formation5
This paper delineates and analyzes the SDRTV-to-HDRTV conversion by modeling the formation of SDRTV/HDRTV content, and proposes a new three-step solution called HDRTVNet++, which includes adaptive global color mapping, local enhancement, and highlight refinement.
- SimpleGVR: A Simple Baseline for Latent-Cascaded Video Super-Resolution5
This work establishes a simple yet effective baseline for cascaded video super-resolution generation, offering practical insights to guide future advancements in efficient cascaded synthesis systems.
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- A Saliency Dataset of Head and Eye Movements for Augmented Reality.4
To bridge the gap between the real-world scene and the scene augmented by virtual information, the ARVR saliency dataset is constructed with 100 diverse videos evaluated by 20 people and annotations of object recognition and tracking as augmented contents are blended into the omnidirectional videos.
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- Reducing the ciphertext expansion in image homomorphic encryption via linear interpolation technique4
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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