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Found 11 papers, 5 papers with code
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.
Frequency Compensated Diffusion Model for Real-scene Dehazing
In this paper, we consider a dehazing framework based on conditional diffusion models for improved generalization to real haze.
Evaluating Instruction-Tuned Large Language Models on Code Comprehension and Generation
First, for the zero-shot setting, instructed LLMs are very competitive on code comprehension and generation tasks and sometimes even better than small SOTA models specifically fine-tuned on each downstream task.
Channel Measurement, Modeling, and Simulation for 6G: A Survey and Tutorial
Then, a survey of the progress of the 6G channel research regarding the above five promising technologies is presented in terms of the latest measurement campaigns, new characteristics, modeling methods, and research prospects.
A Shared Cluster-based Stochastic Channel Model for Joint Communication and Sensing Systems
Then, a stochastic JCAS channel model is proposed to capture the sharing feature, where shared and non-shared clusters by the two channels are defined and superimposed.
Learning to Evaluate Performance of Multi-modal Semantic Localization
Finally, we analyze the SeLo performance of RS cross-modal retrieval models in detail, explore the impact of different variables on this task, and provide a complete benchmark for the SeLo task.
Bidirectional Feature Globalization for Few-shot Semantic Segmentation of 3D Point Cloud Scenes
With prototype-to-point globalization (Pr2PoG), the global perception is embedded to local point features based on similarity weights from sparse prototypes to dense point features.
Remote Sensing Cross-Modal Text-Image Retrieval Based on Global and Local Information
In this article, we first propose a novel RSCTIR framework based on global and local information (GaLR), and design a multi-level information dynamic fusion (MIDF) module to efficaciously integrate features of different levels.
Ranked #6 on
Cross-Modal Retrieval
on RSITMD
Exploring a Fine-Grained Multiscale Method for Cross-Modal Remote Sensing Image Retrieval
Our model adapts to multi-scale feature inputs, favors multi-source retrieval methods, and can dynamically filter redundant features.
Ranked #8 on
Cross-Modal Retrieval
on RSITMD
Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation
We leverage the pixel-level L2 loss and the pixel contrastive loss for the two purposes respectively.
Semantically Robust Unpaired Image Translation for Data with Unmatched Semantics Statistics
Many applications of unpaired image-to-image translation require the input contents to be preserved semantically during translations.
