SOTAVerified

Image Cropping

Image Cropping is a common photo manipulation process, which improves the overall composition by removing unwanted regions. Image Cropping is widely used in photographic, film processing, graphic design, and printing businesses.

Source: Listwise View Ranking for Image Cropping

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 83 papers

TitleStatusHype
A new Level-set based Protocol for Accurate Bone Segmentation from CT Imaging—0
An Experience-based Direct Generation approach to Automatic Image Cropping—0
Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset—0
Automatic Image Cropping : A Computational Complexity Study—0
Automatic Image Cropping for Visual Aesthetic Enhancement Using Deep Neural Networks and Cascaded Regression—0
Boosted EfficientNet: Detection of Lymph Node Metastases in Breast Cancer Using Convolutional Neural Network—0
Boosting Resolution Generalization of Diffusion Transformers with Randomized Positional Encodings—0
Camera View Adjustment Prediction for Improving Image Composition—0
Challenges of building medical image datasets for development of deep learning software in stroke—0
ClipCrop: Conditioned Cropping Driven by Vision-Language Model—0
Comparative Study and Optimization of Feature-Extraction Techniques for Content based Image Retrieval—0
Cropper: Vision-Language Model for Image Cropping through In-Context Learning—0
Data Augmentation using Random Image Cropping for High-resolution Virtual Try-On (VITON-CROP)—0
Deep Learning based CNN Model for Classification and Detection of Individuals Wearing Face Mask—0
Enhancing DR Classification with Swin Transformer and Shifted Window Attention—0
Find Beauty in the Rare: Contrastive Composition Feature Clustering for Nontrivial Cropping Box Regression—0
Good View Hunting: Learning Photo Composition From Dense View Pairs—0
GridNet with automatic shape prior registration for automatic MRI cardiac segmentation—0
Learning the Change for Automatic Image Cropping—0
Leveraging Semi-Supervised Graph Learning for Enhanced Diabetic Retinopathy Detection—0
Lightweight High-Performance Blind Image Quality Assessment—0
Low Cost Machine Vision for Insect Classification—0
RWN: Robust Watermarking Network for Image Cropping Localization—0
Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation—0
Pseudo-Labeling by Multi-Policy Viewfinder Network for Image Cropping—0
Show:102550
← PrevPage 2 of 4Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CACNetBDE0.03—Unverified