Image Cropping
35 papers with code • 1 benchmarks • 4 datasets
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.
Libraries
Use these libraries to find Image Cropping models and implementations
AADB
CUHK Image Cropping
GNMC
Latest papers
From Image to Imuge: Immunized Image Generation
yingqichao/From-Image-to-Imuge-Immunized-Image-Generation
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At the recipient's side, the verifying network localizes the malicious modifications, and the original content can be approximately recovered by the decoder, despite the presence of the attacks.
Looking Outside the Window: Wide-Context Transformer for the Semantic Segmentation of High-Resolution Remote Sensing Images
ggsDing/WiCoNet
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To overcome this limitation, we propose a Wide-Context Network (WiCoNet) for the semantic segmentation of HR RSIs.
Composing Photos Like a Photographer
bo-zhang-cs/CACNet-Pytorch
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CVPR 2021
To this end, we introduce the concept of the key composition map (KCM) to encode the composition rules.
Salient Object Ranking with Position-Preserved Attention
EricFH/salient_object_ranking_with_PPA
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ICCV 2021
In this paper, we study the Salient Object Ranking (SOR) task, which manages to assign a ranking order of each detected object according to its visual saliency.
Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency
However, we demonstrate that formalized fairness metrics and quantitative analysis on their own are insufficient for capturing the risk of representational harm in automatic cropping.
Dissecting Image Crops
basilevh/dissecting-image-crops
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ICCV 2021
The elementary operation of cropping underpins nearly every computer vision system, ranging from data augmentation and translation invariance to computational photography and representation learning.
Towards Resolving the Challenge of Long-tail Distribution in UAV Images for Object Detection
we1pingyu/DSHNet
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To this end, we rethink long-tailed object detection in UAV images and propose the Dual Sampler and Head detection Network (DSHNet), which is the first work that aims to resolve long-tail distribution in UAV images.
A survey on Kornia: an Open Source Differentiable Computer Vision Library for PyTorch
kornia/kornia
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This work presents Kornia, an open source computer vision library built upon a set of differentiable routines and modules that aims to solve generic computer vision problems.
IDA: Improved Data Augmentation Applied to Salient Object Detection
VRI-UFPR/IDA
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Combining our method with others surpasses traditional techniques such as horizontal-flip in 0. 52% for F-measure and 1. 19% for Precision.
Learning to Learn Cropping Models for Different Aspect Ratio Requirements
junjzhang/MetaCropper
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CVPR 2020
In addition, both the intermediate and final results show that the proposed model can predict different cropping windows for an image depending on different aspect ratio requirements.
