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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 1–25 of 83 papers

TitleStatusHype
Enhancing DR Classification with Swin Transformer and Shifted Window Attention—0
Boosting Resolution Generalization of Diffusion Transformers with Randomized Positional Encodings—0
ACE: Anatomically Consistent Embeddings in Composition and DecompositionCode0
FiTv2: Scalable and Improved Flexible Vision Transformer for Diffusion ModelCode3
Cropper: Vision-Language Model for Image Cropping through In-Context Learning—0
Hallu-PI: Evaluating Hallucination in Multi-modal Large Language Models within Perturbed InputsCode1
Understanding the Dependence of Perception Model Competency on Regions in an ImageCode0
Pseudo-Labeling by Multi-Policy Viewfinder Network for Image Cropping—0
Low Cost Machine Vision for Insect Classification—0
FiT: Flexible Vision Transformer for Diffusion ModelCode3
Spatial-Semantic Collaborative Cropping for User Generated ContentCode2
Learning Subject-Aware Cropping by Outpainting Professional Photos—0
Deep Learning based CNN Model for Classification and Detection of Individuals Wearing Face Mask—0
Image Cropping under Design Constraints—0
Challenges of building medical image datasets for development of deep learning software in stroke—0
Beyond Image Borders: Learning Feature Extrapolation for Unbounded Image CompositionCode1
Leveraging Semi-Supervised Graph Learning for Enhanced Diabetic Retinopathy Detection—0
Tame a Wild Camera: In-the-Wild Monocular Camera CalibrationCode1
MixPro: Data Augmentation with MaskMix and Progressive Attention Labeling for Vision TransformerCode1
Construction of unbiased dental template and parametric dental model for precision digital dentistryCode0
Lightweight High-Performance Blind Image Quality Assessment—0
Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection StrategyCode1
Find Beauty in the Rare: Contrastive Composition Feature Clustering for Nontrivial Cropping Box Regression—0
Image Cropping With Spatial-Aware Feature and Rank Consistency—0
An Experience-based Direct Generation approach to Automatic Image Cropping—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CACNetBDE0.03—Unverified