sunghoonim / awesome-image-inpainting

Awesome-Inpainting-Tech

A curated list of inpainting papers and resources, inspired by awesome-computer-vision.

Contents

• Image Inpainting
• Video Inpainting
• Challenge

Image Inpainting

Classical methods (Non-learning based)

1. Image inpainting. Bertalmio, M., Sapiro, G., Caselles, V., & Ballester, C. SIGGRAPH2000.
2. Simultaneous structure and texture image inpainting. Bertalmio, M., Vese, L., Sapiro, G., & Osher, S. TIP2003.
3. Region filling and object removal by exemplar-based image inpainting. Criminisi, A., Pérez, P., & Toyama, K. TIP2004.
4. Image completion with structure propagation. Sun, J., Yuan, L., Jia, J., & Shum, H. Y. TOG2005.
5. Image completion using planar structure guidance. Huang, J. B., Kang, S. B., Ahuja, N., & Kopf, J. TOG2014. [code] [project]

Deep Architectures (Learning Based)

1. Shepard convolutional neural networks. Ren, J. S., Xu, L., Yan, Q., & Sun, W. NeurIPS2015. [code]
2. Context encoders: Feature learning by inpainting. Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., & Efros, A. A. CVPR2016. [code]
3. Globally and locally consistent image completion. Iizuka, S., Simo-Serra, E., & Ishikawa, H. (2017). TOG2017. [code] [project]
4. High-resolution image inpainting using multi-scale neural patch synthesis. Yang, C., Lu, X., Lin, Z., Shechtman, E., Wang, O., & Li, H. CVPR2017. [code]
5. Generative face completion. Li, Y., Liu, S., Yang, J., & Yang, M. H. CVPR2017. [code]
6. Semantic image inpainting with deep generative models. Yeh, R. A., Chen, C., Yian Lim, T., Schwing, A. G., Hasegawa-Johnson, M., & Do, M. N. CVPR2017. [code] [project]
7. Generative image inpainting with contextual attention. Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., & Huang, T. S. CVPR2018. [code] [project]
8. Natural and effective obfuscation by head inpainting. Sun Qianru et al. CVPR2018.
9. Eye in-painting with exemplar generative adversarial networks. Dolhansky, B., & Canton Ferrer, C. CVPR2018. [project] [code]
10. Uv-gan: Adversarial facial uv map completion for pose-invariant face recognition. Deng, J., Cheng, S., Xue, N., Zhou, Y., & Zafeiriou, S. CVPR2018.
11. Disentangling Structure and Aesthetics for Style-aware Image Completion. Gilbert, A., Collomosse, J., Jin, H., & Price, B. CVPR2018.
12. Image inpainting for irregular holes using partial convolutions. Liu, G., Reda, F. A., Shih, K. J., Wang, T. C., Tao, A., & Catanzaro, B. ECCV2018. [project]
13. Contextual-based image inpainting: Infer, match, and translate. Song, Y., Yang, C., Lin, Z., Liu, X., Huang, Q., Li, H., & Jay Kuo, C. C. ECCV2018.
14. Shift-net: Image inpainting via deep feature rearrangement. Yan, Z., Li, X., Li, M., Zuo, W., & Shan, S. ECCV2018. [code]
15. Image Inpainting via Generative Multi-column Convolutional Neural Networks. Wang, Y., Tao, X., Qi, X., Shen, X., & Jia, J. NeurIPS2018. [code]
16. SPG-Net: Segmentation prediction and guidance network for image inpainting. Song, Y., Yang, C., Shen, Y., Wang, P., Huang, Q., & Kuo, C. C. J. BMVC2018.
17. Structural inpainting. Vo, H. V., Duong, N. Q., & Pérez, P. MM2018.
18. Semantic Image Inpainting with Progressive Generative Networks. Zhang, H., Hu, Z., Luo, C., Zuo, W., & Wang, M. MM2018. [code]
19. Face Completion with Semantic Knowledge and Collaborative Adversarial Learning. Liao, H., Funka-Lea, G., Zheng, Y., Luo, J., & Zhou, S. K. ACCV2018.
20. Edge-Aware Context Encoder for Image Inpainting. Liao, L., Hu, R., Xiao, J., & Wang, Z. ICASPP2018.
21. Faceshop: Deep sketch-based face image editing. Portenier, T., Hu, Q., Szabó, A., Bigdeli, S. A., Favaro, P., & Zwicker, M. TOG2018.
22. High resolution face completion with multiple controllable attributes via fully end-to-end progressive generative adversarial networks. Chen, Z., Nie, S., Wu, T., & Healey, C. G. Arxiv2018.
23. On Hallucinating Context and Background Pixels from a Face Mask using Multi-scale GANs. Banerjee, S., Scheirer, W. J., Bowyer, K. W., & Flynn, P. J. Arxiv2018.
24. Free-form image inpainting with gated convolution. Yu, J., Lin, Z., Yang, J., Shen, X., Lu, X., & Huang, T. S. Arxiv2018. [project]
25. Pluralistic Image Completion. Zheng, C., Cham, T. J., & Cai, J. CVPR2019. [code] [project]
26. Learning Pyramid-Context Encoder Network for High-Quality Image Inpainting. Zeng, Y., Fu, J., Chao, H., & Guo, B. CVPR2019. [code]
27. Foreground-aware Image Inpainting. Xiong, W., Lin, Z., Yang, J., Lu, X., Barnes, C., & Luo, J. CVPR2019.
28. Deep Reinforcement Learning of Volume-guided Progressive View Inpainting for 3D Point Scene Completion from a Single Depth Image. Han, X., Zhang, Z., Du, D., Yang, M., Yu, J., Pan, P., ... & Cui, S. CVPR2019.
29. PEPSI: Fast Image Inpainting With Parallel Decoding Network. CVPR (pp. 11360-11368). Sagong, M. C., Shin, Y. G., Kim, S. W., Park, S., & Ko, S. J. CVPR2019.
30. Coordinate-Based Texture Inpainting for Pose-Guided Human Image Generation. Grigorev, A., Sevastopolsky, A., Vakhitov, A., & Lempitsky, V. CVPR2019.
31. EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning. Nazeri, K., Ng, E., Joseph, T., Qureshi, F., & Ebrahimi, M. Arxiv2019. [code]
32. Deep Inception Generative Network for Cognitive Image Inpainting. Xiao, Q., Li, G., & Chen, Q. Arxiv2019.
33. Detecting Overfitting of Deep Generative Networks via Latent Recovery. Webster, R., Rabin, J., Simon, L., & Jurie, F. Arxiv2019.
34. SC-FEGAN: Face Editing Generative Adversarial Network with User's Sketch and Color. Jo, Y., & Park, J. (2019). Arxiv2019. [code]
35. Deep Fusion Network for Image Completion. Hong, X., Xiong, P., Ji, R., & Fan, H. Arxiv2019. [code]
36. PEPSI++: Fast and Lightweight Network for Image Inpainting. Shin, Y. G., Sagong, M. C., Yeo, Y. J., Kim, S. W., & Ko, S. J. Arxiv2019.

Video Inpainting

Classical methods (Non-learning based)

1. Background inpainting for videos with dynamic objects and a free-moving camera. Springer, Berlin, Heidelberg. Granados, M., Kim, K. I., Tompkin, J., Kautz, J., & Theobalt, C. ECCV2012. [project]
2. Video inpainting of complex scenes. Newson, A., Almansa, A., Fradet, M., Gousseau, Y., & Pérez, P. SIAM Journal on Imaging Sciences, 7(4), 1993-2019. [project]
3. Temporally coherent completion of dynamic video. Huang, J. B., Kang, S. B., Ahuja, N., & Kopf, J. TOG2016. [project] [code]

Deep Architectures (Learning Based)

1. Video inpainting by jointly learning temporal structure and spatial details. Wang, C., Huang, H., Han, X., & Wang, J. Arxiv2018.
2. Deep Flow-Guided Video Inpainting. Xu, R., Li, X., Zhou, B., & Loy, C. C. CVPR2019. [code] [project]
3. Deep Video Inpainting. Kim, D., Woo, S., Lee, J. Y., & Kweon, I. S. CVPR2019. [code]
4. Deep Blind Video Decaptioning by Temporal Aggregation and Recurrence. Kim, D., Woo, S., Lee, J. Y., & Kweon, I. S. CVPR2019.
5. Align-and-Attend Network for Globally and Locally Coherent Video Inpainting. Woo, S., Kim, D., Park, K., Lee, J. Y., & Kweon, I. S. Arxiv2019.

Challenge

1. 2018 Looking at People ECCV Satellite Challenge