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Found 20 papers, 8 papers with code
E4C: Enhance Editability for Text-Based Image Editing by Harnessing Efficient CLIP Guidance
Diffusion-based image editing is a composite process of preserving the source image content and generating new content or applying modifications.
Augmenting Prototype Network with TransMix for Few-shot Hyperspectral Image Classification
However, observing the classification results of existing methods, we found that boundary patches corresponding to the pixels which are located at the boundary of the objects in the hyperspectral images, are hard to classify.
Iterative missing value imputation based on feature importance
Existing imputation methods estimate the missing parts based on the observed values in the original feature space, and they treat all features as equally important during data completion, while in fact different features have different importance.
Multi-level Relation Learning for Cross-domain Few-shot Hyperspectral Image Classification
In addition, it adopts a transformer based cross-attention learning module to learn the set-level sample relations and acquire the attention from query samples to support samples.
VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence
To be commensurate with this capacity, in addition to the real data used for pre-training, we also generated and leveraged synthetic ophthalmic imaging data.
Multi-level Cross-modal Feature Alignment via Contrastive Learning towards Zero-shot Classification of Remote Sensing Image Scenes
To address the zero-shot image scene classification, the cross-modal feature alignment methods have been proposed in recent years.
CoT-MISR:Marrying Convolution and Transformer for Multi-Image Super-Resolution
How to transform a low-resolution image to restore its high-resolution image information is a problem that researchers have been exploring.
Faster Learning of Temporal Action Proposal via Sparse Multilevel Boundary Generator
Temporal action localization in videos presents significant challenges in the field of computer vision.
ISTVT: Interpretable Spatial-Temporal Video Transformer for Deepfake Detection
To address these two challenges, in this paper, we propose an Interpretable Spatial-Temporal Video Transformer (ISTVT), which consists of a novel decomposed spatial-temporal self-attention and a self-subtract mechanism to capture spatial artifacts and temporal inconsistency for robust Deepfake detection.
UV R-CNN: Stable and Efficient Dense Human Pose Estimation
Dense pose estimation is a dense 3D prediction task for instance-level human analysis, aiming to map human pixels from an RGB image to a 3D surface of the human body.
SGM-Net: Semantic Guided Matting Net
When the green screen is not available, the existing human matting methods need the help of additional inputs (such as trimap, background image, etc.
A Deterministic Sampling Method via Maximum Mean Discrepancy Flow with Adaptive Kernel
We propose a novel deterministic sampling method to approximate a target distribution $\rho^*$ by minimizing the kernel discrepancy, also known as the Maximum Mean Discrepancy (MMD).
A phase field model for mass transport with semi-permeable interfaces
Numerical simulations first illustrate the consistency of theoretical results on the sharp interface limit.
Numerical Analysis Numerical Analysis 76Z99, 92B05, 76R50
Global Existence of Classical Solutions for a Reactive Polymeric Fluid near Equilibrium
In this paper, we study a new micro-macro model for a reactive polymeric fluid, which is derived recently in [Y. Wang, T.-F. Zhang, and C. Liu, \emph{J. Non-Newton.
Analysis of PDEs 35A01, 35A15, 76A10, 76M30, 82D60
Renovating Parsing R-CNN for Accurate Multiple Human Parsing
Multiple human parsing aims to segment various human parts and associate each part with the corresponding instance simultaneously.
Particle-based Energetic Variational Inference
Using the EVI framework, we can derive many existing Particle-based Variational Inference (ParVI) methods, including the popular Stein Variational Gradient Descent (SVGD) approach.
CPM R-CNN: Calibrating Point-guided Misalignment in Object Detection
In object detection, offset-guided and point-guided regression dominate anchor-based and anchor-free method separately.
High-speed Railway Fastener Detection and Localization Method based on convolutional neural network
Railway transportation is the artery of China's national economy and plays an important role in the development of today's society.
Leveraging Crowdsourced GPS Data for Road Extraction from Aerial Imagery
Deep learning is revolutionizing the mapping industry.
On the performance of different mutation operators of a subpopulation-based genetic algorithm for multi-robot task allocation problems
The performance of different mutation operators in solving problems without/with cooperative tasks is evaluated.
