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Found 4 papers, 2 papers with code
Finding More Relevance: Propagating Similarity on Markov Random Field for Image Retrieval
To effectively retrieve objects from large corpus with high accuracy is a challenge task.
An End-to-End Neural Network for Image Cropping by Learning Composition from Aesthetic Photos
In this paper, we primarily focus on improving the accuracy of automatic image cropping, and on further exploring its potential in public datasets with high efficiency.
Weakly Supervised Real-time Image Cropping based on Aesthetic Distributions
In order to tackle this problem, a weakly supervised cropping frame- work is proposed, where the distribution dissimilarity between high quality images and cropped images is used to guide the coordinate predictor’s training and the ground truths of cropping windows are not required by the proposed method.
Self-supervised Photographic Image Layout Representation Learning
This shortfall makes the learning process for photographic image layouts suboptimal.
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