Search Results for author:
Found 10 papers, 5 papers with code
WiMANS: A Benchmark Dataset for WiFi-based Multi-user Activity Sensing
WiFi-based human sensing has exhibited remarkable potential to analyze user behaviors in a non-intrusive and device-free manner, benefiting applications as diverse as smart homes and healthcare.
CommIN: Semantic Image Communications as an Inverse Problem with INN-Guided Diffusion Models
In this work, we propose CommIN, which views the recovery of high-quality source images from degraded reconstructions as an inverse problem.
INDigo: An INN-Guided Probabilistic Diffusion Algorithm for Inverse Problems
With the help of INN, our algorithm effectively estimates the details lost in the degradation process and is no longer limited by the requirement of knowing the closed-form expression of the degradation model.
AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation
The acquired disease-grounded visual features can better represent the abnormal regions of the input image, which could alleviate data bias problem; 2) MGT module effectively uses the multi-grained features and Transformer framework to generate the long medical report.
COAST: COntrollable Arbitrary-Sampling NeTwork for Compressive Sensing
In this paper, we propose a novel COntrollable Arbitrary-Sampling neTwork, dubbed COAST, to solve CS problems of arbitrary-sampling matrices (including unseen sampling matrices) with one single model.
NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results
This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results.
ISTA-Net++: Flexible Deep Unfolding Network for Compressive Sensing
While deep neural networks have achieved impressive success in image compressive sensing (CS), most of them lack flexibility when dealing with multi-ratio tasks and multi-scene images in practical applications.
Quaternion-Based Self-Attentive Long Short-Term User Preference Encoding for Recommendation
Quaternion space has brought several benefits over the traditional Euclidean space: Quaternions (i) consist of a real and three imaginary components, encouraging richer representations; (ii) utilize Hamilton product which better encodes the inter-latent interactions across multiple Quaternion components; and (iii) result in a model with smaller degrees of freedom and less prone to overfitting.
Attributed Multi-Relational Attention Network for Fact-checking URL Recommendation
To combat fake news, researchers mostly focused on detecting fake news and journalists built and maintained fact-checking sites (e. g., Snopes. com and Politifact. com).
Bridging the Gap between Training and Inference for Neural Machine Translation
Neural Machine Translation (NMT) generates target words sequentially in the way of predicting the next word conditioned on the context words.
