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Found 74 papers, 18 papers with code
Multi-Modal Large Models Based Beam Prediction: An Example Empowered by DeepSeek
Additionally, it demonstrates few-shot generalization on a real-world dataset, achieving 72. 7% Top-1 accuracy and 92. 4% Top-3 accuracy with only 30% of the dataset, outperforming the existing small models by over 15%.
A Unified RCS Modeling of Typical Targets for 3GPP ISAC Channel Standardization and Experimental Analysis
Accurate radar cross section (RCS) modeling is crucial for characterizing target scattering and improving the precision of Integrated Sensing and Communication (ISAC) channel modeling.
A Unified Deterministic Channel Model for Multi-Type RIS with Reflective, Transmissive, and Polarization Operations
RIS can be categorized into multiple types based on their reflective/transmissive modes and polarization control capabilities, all of which are expected to be widely deployed in practical environments.
Text-Audio-Visual-conditioned Diffusion Model for Video Saliency Prediction
Therefore, we attempt to simultaneously analyze visual, auditory, and textual modalities in this paper, and propose TAVDiff, a Text-Audio-Visual-conditioned Diffusion Model for video saliency prediction.
DVLTA-VQA: Decoupled Vision-Language Modeling with Text-Guided Adaptation for Blind Video Quality Assessment
Inspired by the dual-stream theory of the human visual system (HVS) - where the ventral stream is responsible for object recognition and detail analysis, while the dorsal stream focuses on spatial relationships and motion perception - an increasing number of video quality assessment (VQA) works built upon this framework are proposed.
FANeRV: Frequency Separation and Augmentation based Neural Representation for Video
Neural representations for video (NeRV) have gained considerable attention for their strong performance across various video tasks.
Covariance-Intersection-based Distributed Kalman Filtering: Stability Problems Revisited
For the periodic time-varying case, it is proved by a monotonicity analysis method that CI-based distributed Kalman filtering converges periodically for any initial condition.
FedPCA: Noise-Robust Fair Federated Learning via Performance-Capacity Analysis
In this paper, we attribute this competition to the homogeneity in loss patterns exhibited by rare and mislabeled data clients, preventing existing loss-based fair and robust FL methods from effectively distinguishing and handling these two distinct client types.
Fair Federated Medical Image Classification Against Quality Shift via Inter-Client Progressive State Matching
Existing fair federated learning methods have demonstrated some effectiveness in solving this problem by aligning a single 0th- or 1st-order state of convergence (e. g., training loss or sharpness).
Distributed Zonotopic Fusion Estimation for Multi-sensor Systems
To reduce the conservatism of the DZFE with optimal parameters, we enhance our approach with an improved zonotope fusion criterion, which further improves the estimation performance of this DZFE by constructing tight strips for the intersection.
Road to 6G Digital Twin Networks: Multi-Task Adaptive Ray-Tracing as a Key Enabler
As a virtual, synchronized replica of physical network, the digital twin network (DTN) is envisioned to sense, predict, optimize and manage the intricate wireless technologies and architectures brought by 6G.
Structural Pruning via Spatial-aware Information Redundancy for Semantic Segmentation
Within this framework, we introduce a spatial-aware redundancy metric based on feature maps, thus endowing the pruning process with location sensitivity to better adapt to pruning segmentation networks.
CP-DETR: Concept Prompt Guide DETR Toward Stronger Universal Object Detection
In addition to text prompts, we have designed two practical concept prompt generation methods, visual prompt and optimized prompt, to extract abstract concepts through concrete visual examples and stably reduce alignment bias in downstream tasks.
Ranked #1 on
Zero-Shot Object Detection
on LVIS v1.0 val
(using extra training data)
Multi-Modal Environmental Sensing Based Path Loss Prediction for V2I Communications
The stability and reliability of wireless data transmission in vehicular networks face significant challenges due to the high dynamics of path loss caused by the complexity of rapidly changing environments.
Holmes-VAU: Towards Long-term Video Anomaly Understanding at Any Granularity
For efficient anomaly detection in long videos, we propose the Anomaly-focused Temporal Sampler (ATS).
Relevance-guided Audio Visual Fusion for Video Saliency Prediction
Audio data, often synchronized with video frames, plays a crucial role in guiding the audience's visual attention.
Multi-task Feature Enhancement Network for No-Reference Image Quality Assessment
First, existing methods have not explicitly exploited texture details, which significantly influence the image quality.
High-Frequency Enhanced Hybrid Neural Representation for Video Compression
Next, we design the High-Frequency Feature Modulation (HFM) block, which leverages the extracted high-frequency embeddings to enhance the fitting process of the decoder.
Stability Analysis of Distributed Estimators for Large-Scale Interconnected Systems: Time-Varying and Time-Invariant Cases
Then, the distributed estimator is proved to be stable if the DMRE remains uniformly bounded.
ChannelGPT: A Large Model to Generate Digital Twin Channel for 6G Environment Intelligence
In practice, we also establish a ChannelGPT prototype to generate high-fidelity channel data for varied scenarios to validate the accuracy and generalization ability based on environment intelligence.
Wireless Environment Information Sensing, Feature, Semantic, and Knowledge: Four Steps Towards 6G AI-Enabled Air Interface
The air interface technology plays a crucial role in optimizing the communication quality for users.
Bridging Domain Gap of Point Cloud Representations via Self-Supervised Geometric Augmentation
Recent progress of semantic point clouds analysis is largely driven by synthetic data (e. g., the ModelNet and the ShapeNet), which are typically complete, well-aligned and noisy free.
MSVM-UNet: Multi-Scale Vision Mamba UNet for Medical Image Segmentation
State Space Models (SSMs), especially Mamba, have shown great promise in medical image segmentation due to their ability to model long-range dependencies with linear computational complexity.
Can Wireless Environmental Information Decrease Pilot Overhead: A CSI Prediction Example
Finally, a CNN-based channel prediction network is designed to predict the complete CSI, using the environmental feature map and partial CSI.
PASSION: Towards Effective Incomplete Multi-Modal Medical Image Segmentation with Imbalanced Missing Rates
In this paper, we, for the first time, formulate such a challenging setting and propose Preference-Aware Self-diStillatION (PASSION) for incomplete multi-modal medical image segmentation under imbalanced missing rates.
FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation Completeness
We begin by evaluating the completeness of annotations at the client level using a designed indicator.
FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity
Experiments on two publicly-available medical datasets validate the superiority of FedMLP against the state-of-the-art both federated semi-supervised and noisy label learning approaches under task heterogeneity.
Intermittent Encryption Strategies for Anti-Eavesdropping Estimation
A linear encryption scheme is utilized, which first linearly transforms innovation via an encryption matrix and then encrypts some components of the transformed innovation.
An Enhanced Dynamic Ray Tracing Architecture for Channel Prediction Based on Multipath Bidirectional Geometry and Field Extrapolation
Interestingly, a dynamic ray tracing (DRT) approach for channel prediction has recently been proposed, which utilizes the results of traditional RT to extrapolate the multipath geometry evolution.
Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling
In MDPS, the problem of normal image reconstruction is mathematically modeled as multiple diffusion posterior sampling for normal images based on the devised masked noisy observation model and the diffusion-based normal image prior under Bayesian framework.
From Optimization to Generalization: Fair Federated Learning against Quality Shift via Inter-Client Sharpness Matching
In this study, we pioneer the identification and formulation of this new fairness challenge within the context of the imaging quality shift.
ControlMol: Adding Substructure Control To Molecule Diffusion Models
Due to the vast design space of molecules, generating molecules conditioned on a specific sub-structure relevant to a particular function or therapeutic target is a crucial task in computer-aided drug design.
Pointsoup: High-Performance and Extremely Low-Decoding-Latency Learned Geometry Codec for Large-Scale Point Cloud Scenes
Despite considerable progress being achieved in point cloud geometry compression, there still remains a challenge in effectively compressing large-scale scenes with sparse surfaces.
SAMCT: Segment Any CT Allowing Labor-Free Task-Indicator Prompts
Specifically, based on SAM, SAMCT is further equipped with a U-shaped CNN image encoder, a cross-branch interaction module, and a task-indicator prompt encoder.
Digital Twin Channel for 6G: Concepts, Architectures and Potential Applications
Digital twin channel (DTC) is the real-time mapping of a wireless channel from the physical world to the digital world, which is expected to provide significant performance enhancements for the sixth-generation (6G) air-interface design.
Joint End-to-End Image Compression and Denoising: Leveraging Contrastive Learning and Multi-Scale Self-ONNs
Noisy images are a challenge to image compression algorithms due to the inherent difficulty of compressing noise.
Panoramic Image Inpainting With Gated Convolution And Contextual Reconstruction Loss
In response to these challenges, we propose a panoramic image inpainting framework that consists of a Face Generator, a Cube Generator, a side branch, and two discriminators.
FedA3I: Annotation Quality-Aware Aggregation for Federated Medical Image Segmentation against Heterogeneous Annotation Noise
Specifically, noise estimation at each client is accomplished through the Gaussian mixture model and then incorporated into model aggregation in a layer-wise manner to up-weight high-quality clients.
Exploration of visual prompt in Grounded pre-trained open-set detection
Text prompts are crucial for generalizing pre-trained open-set object detection models to new categories.
Boosting Facial Action Unit Detection Through Jointly Learning Facial Landmark Detection and Domain Separation and Reconstruction
Recently how to introduce large amounts of unlabeled facial images in the wild into supervised Facial Action Unit (AU) detection frameworks has become a challenging problem.
Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting
End-to-end medical image segmentation is of great value for computer-aided diagnosis dominated by task-specific models, usually suffering from poor generalization.
ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation
Following CSA, 2D convolution is utilized for feature refinement through CFFN.
Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning
We further show that this method is guaranteed to converge to the optimal policy, which cannot be achieved by previous value-based reinforcement learning methods for marketing budget allocation.
Carbon emissions and sustainability of launching 5G mobile networks in China
We show that the decline in carbon efficiency leads to a carbon efficiency trap, estimated to cause additional carbon emissions of 23. 82 +- 1. 07 megatons in China.
DataAI-6G: A System Parameters Configurable Channel Dataset for AI-6G Research
A common and accurate dataset is essential for the research of AI communication.
MAMIQA: No-Reference Image Quality Assessment Based on Multiscale Attention Mechanism With Natural Scene Statistics
No-Reference Image Quality Assessment aims to evaluate the perceptual quality of an image, according to human perception.
FedNoRo: Towards Noise-Robust Federated Learning by Addressing Class Imbalance and Label Noise Heterogeneity
Federated noisy label learning (FNLL) is emerging as a promising tool for privacy-preserving multi-source decentralized learning.
Spatiotemporally Consistent HDR Indoor Lighting Estimation
For training, we significantly enhance the OpenRooms public dataset of photorealistic synthetic indoor scenes with around 360K HDR environment maps of much higher resolution and 38K video sequences, rendered with GPU-based path tracing.
Remote State Estimation with Posterior-Based Stochastic Event-Triggered Schedule
A posterior-based SET mechanism is proposed, which determines whether to transmit data by the effect of the measurement on the posterior estimate.
Cross-Fusion Rule for Personalized Federated Learning
To overcome these challenges, a multi-layer multi-fusion strategy framework is proposed in this paper, i. e., the server adopts the network layer parameters of each client upload model as the basic unit of fusion for information-sharing calculation.
Learning stability of partially observed switched linear systems
In this paper, we propose an algorithm for deciding stability of switched linear systems under arbitrary switching based purely on observed output data.
Hand Gesture Recognition through Reflected Infrared Light Wave Signals
In this study, we present a wireless (non-contact) gesture recognition method using only incoherent light wave signals reflected from a human subject.
Secure Fusion Estimation Against FDI Sensor Attacks in Cyber-Physical Systems
This paper is concerned with the problem of secure multi-sensors fusion estimation for cyber-physical systems, where sensor measurements may be tampered with by false data injection (FDI) attacks.
End-to-end Transformer for Compressed Video Quality Enhancement
In this work, we propose a transformer-based compressed video quality enhancement (TVQE) method, consisting of Swin-AutoEncoder based Spatio-Temporal feature Fusion (SSTF) module and Channel-wise Attention based Quality Enhancement (CAQE) module.
How to Define the Propagation Environment Semantics and Its Application in Scatterer-Based Beam Prediction
Inspired by task-oriented semantic communication and machine learning (ML) powered environment-channel mapping methods, this work aims to provide a new view of the environment from the semantic level, which defines the propagation environment semantics (PES) as a limited set of propagation environment semantic symbols (PESS) for diverse application tasks.
Distributed Event-Triggered Nonlinear Fusion Estimation under Resource Constraints
This paper studies the event-triggered distributed fusion estimation problems for a class of nonlinear networked multisensor fusion systems without noise statistical characteristics.
Frequency-Angle Two-Dimensional Reflection Coefficient Modeling Based on Terahertz Channel Measurement
In this letter, the reflection coefficient of the THz channel is researched based on extensive measurement campaigns.
The Lighter The Better: Rethinking Transformers in Medical Image Segmentation Through Adaptive Pruning
To our best knowledge, this is the first work on transformer pruning for medical image analysis tasks.
BATFormer: Towards Boundary-Aware Lightweight Transformer for Efficient Medical Image Segmentation
Specifically, to fully explore the benefits of transformers in long-range dependency establishment, a cross-scale global transformer (CGT) module is introduced to jointly utilize multiple small-scale feature maps for richer global features with lower computational complexity.
FedIIC: Towards Robust Federated Learning for Class-Imbalanced Medical Image Classification
In this paper, we present a privacy-preserving FL method named FedIIC to combat class imbalance from two perspectives: feature learning and classifier learning.
Distributed Estimation for Interconnected Systems with Arbitrary Coupling Structures
By merging these subsystem-level stability conditions and the optimization-based estimator gain design, the distributed, stable and optimal estimators are proposed.
Surface Defect Detection and Evaluation for Marine Vessels using Multi-Stage Deep Learning
Detecting and evaluating surface coating defects is important for marine vessel maintenance.
Adversarial Learning for Incentive Optimization in Mobile Payment Marketing
This bias deteriorates the performance of the response model and misleads the linear programming process, dramatically degrading the performance of the resulting allocation policy.
Kalman-Like Filter under Binary Sensors
When considering linear dynamic systems, a conservative estimation error covariance with adjustable parameters is constructed by matrix inequality, and then an optimal filter gain is derived by minimizing its trace.
Enhanced Sequential Covariance Intersection Fusion
For this criterion, it is proved that the fusion results are not affected by the fusion structure, and thus the fusion performance can be guaranteed.
Discrete-continuous Action Space Policy Gradient-based Attention for Image-Text Matching
We propose a novel attention scheme which projects the image and text embedding into a common space and optimises the attention weights directly towards the evaluation metrics.
A generalization of moment-angle manifolds with non-contractible orbit spaces
This generalizes the Hochster's formula for the moment-angle manifold over a simple convex polytope.
Algebraic Topology Geometric Topology 57S12 (Primary) 57N65, 57S17, 57S25 (Secondary)
Noisy Student Training using Body Language Dataset Improves Facial Expression Recognition
Facial expression recognition from videos in the wild is a challenging task due to the lack of abundant labelled training data.
Ranked #7 on
Facial Expression Recognition (FER)
on Acted Facial Expressions In The Wild (AFEW)
(using extra training data)
Facial Expression Recognition
Facial Expression Recognition (FER)
Gesture Recognition using Reflected Visible and Infrared Light Wave Signals
In this paper, we demonstrate the ability to recognize hand gestures in a non-contact, wireless fashion using only incoherent light signals reflected from a human subject.
DA4AD: End-to-End Deep Attention-based Visual Localization for Autonomous Driving
We present a visual localization framework based on novel deep attention aware features for autonomous driving that achieves centimeter level localization accuracy.
Skull-RCNN: A CNN-based network for the skull fracture detection
Guiding by the morphological features of the skull, a skeleton-based region proposal method is proposed to make candidate boxes more concentrated in key regions and reduce invalid boxes.
Accelerate CU Partition in HEVC using Large-Scale Convolutional Neural Network
High efficiency video coding (HEVC) suffers high encoding computational complexity, partly attributed to the rate-distortion optimization quad-tree search in CU partition decision.
Context-Aware Online Learning for Course Recommendation of MOOC Big Data
In this respect, the key challenge is how to realize personalized course recommendation as well as to reduce the computing and storage costs for the tremendous course data.
Monocular Urban Localization using Street View
This paper presents a metric global localization in the urban environment only with a monocular camera and the Google Street View database.
