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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

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Showing 51–83 of 83 papers

TitleStatusHype
Learning Subject-Aware Cropping by Outpainting Professional Photos—0
Learning the Change for Automatic Image Cropping—0
Boosting Resolution Generalization of Diffusion Transformers with Randomized Positional Encodings—0
Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks—0
Leveraging Semi-Supervised Graph Learning for Enhanced Diabetic Retinopathy Detection—0
Lightweight High-Performance Blind Image Quality Assessment—0
Towards Evaluating Gaussian Blurring in Perceptual Hashing as a Facial Image Filter—0
Boosted EfficientNet: Detection of Lymph Node Metastases in Breast Cancer Using Convolutional Neural Network—0
Low Cost Machine Vision for Insect Classification—0
An Automatic Image Content Retrieval Method for better Mobile Device Display User Experiences—0
Automatic Image Cropping for Visual Aesthetic Enhancement Using Deep Neural Networks and Cascaded Regression—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
Traffic Sign Detection and Recognition for Autonomous Driving in Virtual Simulation Environment—0
Weakly Supervised Real-time Image Cropping based on Aesthetic Distributions—0
Repurposing Existing Deep Networks for Caption and Aesthetic-Guided Image Cropping—0
Resnet18 Model With Sequential Layer For Computing Accuracy On Image Classification Dataset—0
Rethinking Image Cropping: Exploring Diverse Compositions From Global Views—0
Image Protection for Robust Cropping Localization and Recovery—0
Automatic Image Cropping : A Computational Complexity Study—0
Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset—0
Semantic Image Cropping—0
An Experience-based Direct Generation approach to Automatic Image Cropping—0
A new Level-set based Protocol for Accurate Bone Segmentation from CT Imaging—0
Towards Domain-Agnostic Contrastive Learning—0
Towards End-to-End Text Spotting in Natural Scenes—0
Find Beauty in the Rare: Contrastive Composition Feature Clustering for Nontrivial Cropping Box Regression—0
Enhancing DR Classification with Swin Transformer and Shifted Window Attention—0
Deep Learning based CNN Model for Classification and Detection of Individuals Wearing Face Mask—0
Data Augmentation using Random Image Cropping for High-resolution Virtual Try-On (VITON-CROP)—0
Good View Hunting: Learning Photo Composition From Dense View Pairs—0
Cropper: Vision-Language Model for Image Cropping through In-Context Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CACNetBDE0.03—Unverified