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Found 22 papers, 6 papers with code
Prompt-enhanced Hierarchical Transformer Elevating Cardiopulmonary Resuscitation Instruction via Temporal Action Segmentation
The vast majority of people who suffer unexpected cardiac arrest are performed cardiopulmonary resuscitation (CPR) by passersby in a desperate attempt to restore life, but endeavors turn out to be fruitless on account of disqualification.
Flocking control against the malicious agent
This paper investigates the flocking control of a swarm with a malicious agent that falsifies its controller parameters to cause collision, division, and escape of agents in the swarm.
Living Images: A Recursive Approach to Computing the Structural Beauty of Images or the Livingness of Space
We applied the recursive approach to a set of images and found that (1) the number of substructures of an image is far lower (3 percent on average) than the number of pixels and the centroids of the substructures can effectively capture the skeleton or saliency of the image; (2) all the images have the recursive levels more than three, indicating that they are indeed living images; (3) no more than 2 percent of the substructures are decomposable; (4) structural beauty can be measured by the recursively defined substructures, as well as their decomposable subsets.
Learning to Dub Movies via Hierarchical Prosody Models
Given a piece of text, a video clip and a reference audio, the movie dubbing (also known as visual voice clone V2C) task aims to generate speeches that match the speaker's emotion presented in the video using the desired speaker voice as reference.
Mixed-UNet: Refined Class Activation Mapping for Weakly-Supervised Semantic Segmentation with Multi-scale Inference
Deep learning techniques have shown great potential in medical image processing, particularly through accurate and reliable image segmentation on magnetic resonance imaging (MRI) scans or computed tomography (CT) scans, which allow the localization and diagnosis of lesions.
Cerebrovascular morphology in aging and disease -- imaging biomarkers for ischemic stroke and Alzheimers disease
Conclusion: Altered vessel geometry in AIS patients shows that there is pathological morphology coupled with stroke.
Structural Beauty: A Structure-based Approach to Quantifying the Beauty of an Image
Based on the concept of living structure, this paper develops an approach for computing the structural beauty or life of an image (L) based on the number of automatically derived substructures (S) and their inherent hierarchy (H).
Mechanical Vibrational Relaxation of NO on Metal and Insulator Surfaces: When and Why Are They Different?
NO scattering from metallic and insulating surfaces represent contrasting benchmark systems for understanding energy transfer at gas-surface interface.
Materials Science Chemical Physics
Learning content and context with language bias for Visual Question Answering
Many works concentrate on how to reduce language bias which makes models answer questions ignoring visual content and language context.
PPGN: Phrase-Guided Proposal Generation Network For Referring Expression Comprehension
Reference expression comprehension (REC) aims to find the location that the phrase refer to in a given image.
PEDNet: A Persona Enhanced Dual Alternating Learning Network for Conversational Response Generation
However, generating personalized responses is still a challenging task since the leverage of predefined persona information is often insufficient.
METNet: A Mutual Enhanced Transformation Network for Aspect-based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) aims to determine the sentiment polarity of each specific aspect in a given sentence.
Aspect-Based Sentiment Analysis (ABSA)
Representation Learning
Determining the effect of hot electron dissipation on molecular scattering experiments at metal surfaces
Nonadiabatic effects that arise from the concerted motion of electrons and atoms at comparable energy and time scales are omnipresent in thermal and light-driven chemistry at metal surfaces.
Materials Science Chemical Physics
Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizations
We use CNN features from the deep and shallow layers of the encoder to represent structures and textures of an input image, respectively.
Regularized L21-Based Semi-NonNegative Matrix Factorization
We present a general-purpose data compression algorithm, Regularized L21 Semi-NonNegative Matrix Factorization (L21 SNF).
One-Stage Inpainting with Bilateral Attention and Pyramid Filling Block
However, the two-stage architecture is time-consuming, the contextual information lack high-level semantics and ignores both the semantic relevance and distance information of hole's feature patches, these limitations result in blurry textures and distorted structures of final result.
Boundary-Aware Salient Object Detection via Recurrent Two-Stream Guided Refinement Network
Recent deep learning based salient object detection methods which utilize both saliency and boundary features have achieved remarkable performance.
Constrained R-CNN: A general image manipulation detection model
Finally, the coarse localization information guides the model to further learn the finer local features and segment out the tampered region.
Context-Integrated and Feature-Refined Network for Lightweight Object Parsing
The core components of CIFReNet are the Long-skip Refinement Module (LRM) and the Multi-scale Context Integration Module (MCIM).
Coherent Semantic Attention for Image Inpainting
The latest deep learning-based approaches have shown promising results for the challenging task of inpainting missing regions of an image.
Ranked #1 on
Image Inpainting
on Paris StreetView
Defining Least Community as a Homogeneous Group in Complex Networks
This notion of far more small things than large ones constitutes a new fundamental way of thinking for community detection.
Physics and Society Social and Information Networks Adaptation and Self-Organizing Systems
Head/tail Breaks: A New Classification Scheme for Data with a Heavy-tailed Distribution
The heavy-tailed distributions are heavily right skewed, with a minority of large values in the head and a majority of small values in the tail, commonly characterized by a power law, a lognormal or an exponential function.
Data Analysis, Statistics and Probability Adaptation and Self-Organizing Systems Physics and Society
