ProCrop uses retrieved professional photos to guide image cropping and introduces a 242,000-image outpainted weakly labeled dataset, reporting state-of-the-art results on standard benchmarks.
Semantic Line Combination Detector
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
A novel algorithm, called semantic line combination detector (SLCD), to find an optimal combination of semantic lines is proposed in this paper. It processes all lines in each line combination at once to assess the overall harmony of the lines. First, we generate various line combinations from reliable lines. Second, we estimate the score of each line combination and determine the best one. Experimental results demonstrate that the proposed SLCD outperforms existing semantic line detectors on various datasets. Moreover, it is shown that SLCD can be applied effectively to three vision tasks of vanishing point detection, symmetry axis detection, and composition-based image retrieval. Our codes are available at https://github.com/Jinwon-Ko/SLCD.
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
ProCrop: Learning Aesthetic Image Cropping from Professional Compositions
ProCrop uses retrieved professional photos to guide image cropping and introduces a 242,000-image outpainted weakly labeled dataset, reporting state-of-the-art results on standard benchmarks.