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Found 8 papers, 4 papers with code
Context-Semantic Quality Awareness Network for Fine-Grained Visual Categorization
To tackle this challenge, we propose a weakly supervised Context-Semantic Quality Awareness Network (CSQA-Net) for FGVC.
Ranked #4 on
Fine-Grained Image Classification
on NABirds
Fine-Grained Image Classification
Fine-Grained Visual Categorization
Robust Transductive Few-shot Learning via Joint Message Passing and Prototype-based Soft-label Propagation
Label propagation methods try to propagate the labels of support samples on the constructed graph encoding the relationships between both support and query samples.
Fine-Grained Visual Classification via Internal Ensemble Learning Transformer
The proposed IELT involves three main modules: multi-head voting (MHV) module, cross-layer refinement (CLR) module, and dynamic selection (DS) module.
Practical Deep Raw Image Denoising on Mobile Devices
Deep learning-based image denoising approaches have been extensively studied in recent years, prevailing in many public benchmark datasets.
Droplets sit and slide anisotropically on soft, stretched substrates
Anisotropically wetting substrates enable useful control of droplet behavior across a range of applications.
Soft Condensed Matter Fluid Dynamics
A Guaranteed Convergence Analysis for the Projected Fast Iterative Soft-Thresholding Algorithm in Parallel MRI
The pFISTA, a simple and efficient algorithm for sparse reconstruction, has been successfully extended to parallel imaging.
Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving Augmentation
In this paper, we present new data pre-processing and augmentation techniques for DNN-based raw image denoising.
Perceive Where to Focus: Learning Visibility-aware Part-level Features for Partial Person Re-identification
The visibility awareness allows VPM to extract region-level features and compare two images with focus on their shared regions (which are visible on both images).
Ranked #14 on
Person Re-Identification
on Market-1501-C
