Awesome Image Composition
Introduction
The Awesome Image Composition project is a carefully curated list of resources dedicated to the art and science of image composition, specifically focusing on object insertion. Image composition involves integrating a foreground object seamlessly into a background to create a realistic composite image by resolving inconsistencies in appearance, geometry, and semantics between the two. This technique is widely used to blend visual elements from different images, offering extensive creative possibilities in the fields of photography, digital art, and beyond.
Contributing to the Project
The project welcomes contributions from enthusiasts and experts alike. If you wish to contribute, you can do so by sending a pull request. Suggestions for new sections or ideas can be discussed by raising an issue before any formal submission.
Key Components of the Project
Online Demo
The project offers an online demo where users can experiment with image composition. This interactive feature provides a firsthand experience of how objects can be skillfully inserted into different backgrounds to achieve a truly harmonious blend.
Survey
A comprehensive survey titled "Making Images Real Again: A Comprehensive Survey on Deep Image Composition" by researchers Li Niu and colleagues provides in-depth insights into the world of deep image composition. The survey is available on arXiv for those who wish to delve deeper into the theoretical aspects.
Toolbox and Resources
The development team has integrated a variety of image composition functions into a toolbox named libcom. This toolbox includes functionalities like image blending, harmonization, shadow generation, and more, streamlining the process of creating complex images with ease.
Research Papers and Topics
The project curates a vast array of research papers covering various aspects of image composition:
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Image Blending: Techniques and new methodologies for seamlessly blending different images.
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Image Harmonization: Ensuring that the tonal and thematic aspects of the composite image are consistent.
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Object Shadow and Reflection Generation: Methods for generating shadows and reflections that contribute to the realism of the composed image.
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Object Placement and Placement Transformation: Strategies for accurately placing objects within a composition and transforming them to fit the space naturally.
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Perspective Transformation: Involves altering an image's perspective to match that of the surrounding elements for a cohesive look.
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Occlusion and Depth Management: Techniques for handling occlusion and depth registration within a composite image.
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Resolution and Noise Management: Addressing issues related to resolution, sharpness, and noise for clearer image quality.
Datasets
The project provides links to datasets pertinent to different aspects of image composition, such as harmonization, shadow generation, object placement, and more. These resources are crucial for training machine learning models and developing new techniques in image composition.
Evaluation
For evaluating the quality and effectiveness of composite images, the project offers access to a dedicated evaluation framework known as Composite-Image-Evaluation.
Conclusion
Awesome Image Composition is a treasure trove for anyone interested in pushing the boundaries of digital art through image composition. By providing a well-rounded suite of resources—from surveys and research papers to datasets and a powerful toolbox—it empowers artists, developers, and researchers to explore, create, and innovate in this exciting field. Whether you're a seasoned professional or a curious newcomer, this project serves as a comprehensive starting point.