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

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Showing 26–50 of 83 papers

TitleStatusHype
Construction of unbiased dental template and parametric dental model for precision digital dentistryCode0
ANDA: A Novel Data Augmentation Technique Applied to Salient Object DetectionCode0
Data Augmentation using Random Image Cropping and Patching for Deep CNNsCode0
An End-to-End Neural Network for Image Cropping by Learning Composition from Aesthetic PhotosCode0
Learning to Learn Cropping Models for Different Aspect Ratio RequirementsCode0
Listwise View Ranking for Image CroppingCode0
Mask Editor : an Image Annotation Tool for Image Segmentation TasksCode0
ACE: Anatomically Consistent Embeddings in Composition and DecompositionCode0
Augmented Balanced Image Dataset Generator Using AugStatic LibraryCode0
Quantitative Analysis of Automatic Image Cropping Algorithms: A Dataset and Comparative StudyCode0
Reliable and Efficient Image Cropping: A Grid Anchor based ApproachCode0
Aesthetic-Driven Image Enhancement by Adversarial LearningCode0
A2-RL: Aesthetics Aware Reinforcement Learning for Image CroppingCode0
Understanding the Dependence of Perception Model Competency on Regions in an ImageCode0
Towards Domain-Agnostic Contrastive Learning—0
Towards End-to-End Text Spotting in Natural Scenes—0
Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks—0
Towards Evaluating Gaussian Blurring in Perceptual Hashing as a Facial Image Filter—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
An Automatic Image Content Retrieval Method for better Mobile Device Display User Experiences—0
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
A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorch—0
Augmentation Techniques Analysis with Removal of Class Imbalance Using PyTorch for Intel Scene Dataset—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CACNetBDE0.03—Unverified