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1 | # Awesome-Object-Insertion 
2 |
3 | **Object insertion/addition/compositing is an alias of [image composition](https://github.com/bcmi/Awesome-Image-Composition).**
4 |
5 | A curated list of resources including papers, datasets, and relevant links pertaining to image composition. **The goal of image composition is inserting one foreground into a background image to get a realistic composite image, by addressing the inconsistencies (appearance, geometry, and semantic inconsistency) between foreground and background.** Generally speaking, image composition could be used to combine the visual elements from different images.
6 |
7 | Welcome to follow WeChat public account ["Newly AIGCer"](https://www.ustcnewly.com/blog.html) or Zhihu Column ["Newly CVer"](https://www.zhihu.com/column/c_1333918224900206592) to get the latest information about image composition!
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13 |
14 | ## Contributing
15 |
16 | Contributions are welcome. If you wish to contribute, feel free to send a pull request. If you have suggestions for new sections to be included, please raise an issue and discuss before sending a pull request.
17 |
18 | ## Table of Contents
19 | + [Online Demo](#Online-demo)
20 | + [Survey](#Survey)
21 | + [Toolbox](#Toolbox)
22 | + [Papers](#Papers)
23 | + [Datasets](#Datasets)
24 | + [Evaluation](#Evaluation)
25 |
26 | ## Online Demo
27 |
28 | Try this [online demo](https://bcmi.sjtu.edu.cn/home/niuli/demo_image_composition/) for image composition and have fun! 
29 |
30 | ## Survey
31 | + Li Niu, Wenyan Cong, Liu Liu, Yan Hong, Bo Zhang, Jing Liang, Liqing Zhang: "*Making Images Real Again: A Comprehensive Survey on Deep Image Composition.*" arXiv preprint arXiv:2106.14490 (2021). [[arXiv]](https://arxiv.org/pdf/2106.14490.pdf) [[slides]](https://www.ustcnewly.com/download/Image_composition_tutorial.pdf)
32 |
33 |
34 | ## Toolbox
35 | We integrate 10+ image composition related functions into [libcom](https://github.com/bcmi/libcom) (the library of image composition), including image blending, standard/painterly image harmonization, shadow generation, object placement, generative composition, quality evaluation, etc. The ultimate goal of this library is solving all the problems related to image composition with simple `import libcom`.
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37 |
38 |
39 | ## Papers
40 |
41 | #### 1. Image Blending
42 | [Awesome-Image-Blending](https://github.com/bcmi/Awesome-Image-Blending)
43 |
44 | #### 2. Image Harmonization
45 | [Awesome-Image-Harmonization](https://github.com/bcmi/Awesome-Image-Harmonization)
46 |
47 | #### 3. Object Shadow Generation
48 | [Awesome-Object-Shadow-Generation](https://github.com/bcmi/Awesome-Object-Shadow-Generation)
49 |
50 | #### 4. Object Reflection Generation
51 | [Awesome-Object-Reflection-Generation](https://github.com/bcmi/Awesome-Object-Reflection-Generation)
52 |
53 | #### 5. Object Placement
54 | [Awesome-Object-Placement](https://github.com/bcmi/Awesome-Object-Placement)
55 |
56 | #### 6. Spatial Transformation
57 | [Awesome-Spatial-Transformation](https://github.com/bcmi/Awesome-Spatial-Transformation)
58 |
59 | #### 7. Occlusion
60 | [Awesome-Composition-Occlusion](https://github.com/bcmi/Awesome-Composition-Occlusion)
61 |
62 | #### 8. Foreground Object Search
63 | [Awesome-Foreground-Object-Search](https://github.com/bcmi/Awesome-Foreground-Object-Search)
64 |
65 | #### 9. Generative Image Composition
66 | [Awesome-Generative-Image-Composition](https://github.com/bcmi/Awesome-Generative-Image-Composition)
67 |
68 | ## Datasets
69 | + Datasets for image harmonization [[link]](https://github.com/bcmi/Awesome-Image-Harmonization#Datasets)
70 | + Datasets for object shadow generation [[link]](https://github.com/bcmi/Awesome-Object-Shadow-Generation#Datasets)
71 | + Datasets for object placement [[link]](https://github.com/bcmi/Awesome-Object-Placement#Datasets)
72 | + Datasets for foreground object search [[link]](https://github.com/bcmi/Awesome-Foreground-Object-Search#Datasets)
73 | + Datasets for perspective transformation [[link]](https://github.com/bcmi/Awesome-Spatial-Transformation#Datasets)
74 | + Datasets for generative image composition [[link]](https://github.com/bcmi/Awesome-Generative-Image-Composition#Datasets)
75 |
76 |
77 | ## Evaluation
78 |
79 | + [Composite-Image-Evaluation](https://github.com/bcmi/Composite-Image-Evaluation)
80 |
81 | ## Other Resources
82 | + [Awesome-Image-Composition](https://github.com/bcmi/Awesome-Image-Composition)
83 |
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