Papers
Topics
Authors
Recent
Search
2000 character limit reached

NTIRE 2024 Restore Any Image Model (RAIM) in the Wild Challenge

Published 16 May 2024 in cs.CV and eess.IV | (2405.09923v1)

Abstract: In this paper, we review the NTIRE 2024 challenge on Restore Any Image Model (RAIM) in the Wild. The RAIM challenge constructed a benchmark for image restoration in the wild, including real-world images with/without reference ground truth in various scenarios from real applications. The participants were required to restore the real-captured images from complex and unknown degradation, where generative perceptual quality and fidelity are desired in the restoration result. The challenge consisted of two tasks. Task one employed real referenced data pairs, where quantitative evaluation is available. Task two used unpaired images, and a comprehensive user study was conducted. The challenge attracted more than 200 registrations, where 39 of them submitted results with more than 400 submissions. Top-ranked methods improved the state-of-the-art restoration performance and obtained unanimous recognition from all 18 judges. The proposed datasets are available at https://drive.google.com/file/d/1DqbxUoiUqkAIkExu3jZAqoElr_nu1IXb/view?usp=sharing and the homepage of this challenge is at https://codalab.lisn.upsaclay.fr/competitions/17632.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (59)
  1. A high-quality denoising dataset for smartphone cameras. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 1692–1700, 2018.
  2. Defocus deblurring using dual-pixel data. In European Conference on Computer Vision, 2020.
  3. NTIRE 2024 dense and non-homogeneous dehazing challenge report. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  4. Nh-haze: An image dehazing benchmark with non-homogeneous hazy and haze-free images. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pages 1798–1805, 2020.
  5. NTIRE 2024 challenge on night photography rendering. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  6. Non-uniform blur kernel estimation via adaptive basis decomposition. arXiv preprint arXiv:2102.01026, 2021.
  7. Deep portrait quality assessment. a NTIRE 2024 challenge survey. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  8. Activating more pixels in image super-resolution transformer. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 22367–22377, 2023.
  9. NTIRE 2024 challenge on image super-resolution (×4): Methods and results. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  10. Masked-attention mask transformer for universal image segmentation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 1290–1299, 2022.
  11. Deep raw image super-resolution. a NTIRE 2024 challenge survey. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  12. Deformable convolutional networks. In Proceedings of the IEEE international conference on computer vision, pages 764–773, 2017.
  13. Aim 2020 challenge on learned image signal processing pipeline. In Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020, Proceedings, Part III 16, pages 152–170. Springer, 2020.
  14. Efficient frequency domain-based transformers for high-quality image deblurring. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 5886–5895, 2023.
  15. Blind face restoration via deep multi-scale component dictionaries. In European conference on computer vision, pages 399–415. Springer, 2020.
  16. NTIRE 2024 challenge on short-form UGC video quality assessment: Methods and results. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  17. Lsdir: A large scale dataset for image restoration. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 1775–1787, 2023.
  18. NTIRE 2024 restore any image model (RAIM) in the wild challenge. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  19. Diffbir: Towards blind image restoration with generative diffusion prior. arXiv preprint arXiv:2308.15070, 2023.
  20. NTIRE 2024 quality assessment of AI-generated content challenge. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024a.
  21. NTIRE 2024 challenge on low light image enhancement: Methods and results. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024b.
  22. Fixing weight decay regularization in adam. 2018.
  23. Controlling vision-language models for universal image restoration. arXiv preprint arXiv:2310.01018, 2023a.
  24. Image restoration with mean-reverting stochastic differential equations. arXiv preprint arXiv:2301.11699, 2023b.
  25. Efficient multi-stage video denoising with recurrent spatio-temporal fusion. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 3466–3475, 2021.
  26. Deep multi-scale convolutional neural network for dynamic scene deblurring. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 257–265, 2016.
  27. Misalignment-robust frequency distribution loss for image transformation. arXiv preprint arXiv:2402.18192, 2024.
  28. Learning degradation uncertainty for unsupervised real-world image super-resolution. In IJCAI, pages 1261–1267, 2022.
  29. Semantic image synthesis with spatially-adaptive normalization. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 2337–2346, 2019.
  30. The ninth NTIRE 2024 efficient super-resolution challenge report. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  31. High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 10684–10695, 2022a.
  32. High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 10684–10695, 2022b.
  33. Learning to deblur using light field generated and real defocus images. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 16283–16292, 2022.
  34. Improving the stability of diffusion models for content consistent super-resolution. arXiv preprint arXiv:2401.00877, 2023.
  35. NTIRE 2024 image shadow removal challenge report. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  36. Exploiting diffusion prior for real-world image super-resolution. arXiv preprint arXiv:2305.07015, 2023a.
  37. Exploiting diffusion prior for real-world image super-resolution. ArXiv, abs/2305.07015, 2023b.
  38. NTIRE 2024 challenge on stereo image super-resolution: Methods and results. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024a.
  39. Real-esrgan: Training real-world blind super-resolution with pure synthetic data. In International Conference on Computer Vision Workshops (ICCVW).
  40. Esrgan: Enhanced super-resolution generative adversarial networks. In The European Conference on Computer Vision Workshops (ECCVW), 2018.
  41. Real-esrgan: Training real-world blind super-resolution with pure synthetic data. In Proceedings of the IEEE/CVF international conference on computer vision, pages 1905–1914, 2021.
  42. NTIRE 2024 challenge on light field image super-resolution: Methods and results. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024b.
  43. Seesr: Towards semantics-aware real-world image super-resolution. arXiv preprint arXiv:2311.16518, 2023.
  44. Diffir: Efficient diffusion model for image restoration. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 13095–13105, 2023.
  45. Segformer: Simple and efficient design for semantic segmentation with transformers. Advances in neural information processing systems, 34:12077–12090, 2021.
  46. Desra: detect and delete the artifacts of gan-based real-world super-resolution models. arXiv preprint arXiv:2307.02457, 2023.
  47. NTIRE 2024 challenge on blind enhancement of compressed image: Methods and results. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  48. Pixel-aware stable diffusion for realistic image super-resolution and personalized stylization. arXiv preprint arXiv:2308.14469, 2023.
  49. Scaling up to excellence: Practicing model scaling for photo-realistic image restoration in the wild. arXiv preprint arXiv:2401.13627, 2024.
  50. NTIRE 2024 challenge on HR depth from images of specular and transparent surfaces. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  51. Restormer: Efficient transformer for high-resolution image restoration. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 5718–5729, 2021.
  52. Restormer: Efficient transformer for high-resolution image restoration. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 5728–5739, 2022.
  53. Learning joint spatial-temporal transformations for video inpainting. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XVI 16, pages 528–543. Springer, 2020.
  54. Aggregated contextual transformations for high-resolution image inpainting. IEEE Transactions on Visualization and Computer Graphics, 2022.
  55. Designing a practical degradation model for deep blind image super-resolution. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 4791–4800, 2021.
  56. Adding conditional control to text-to-image diffusion models. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 3836–3847, 2023a.
  57. Crafting training degradation distribution for the accuracy-generalization trade-off in real-world super-resolution. In International Conference on Machine Learning, pages 41078–41091. PMLR, 2023b.
  58. NTIRE 2024 challenge on bracketing image restoration and enhancement: Datasets, methods and results. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2024.
  59. Srformer: Permuted self-attention for single image super-resolution. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 12780–12791, 2023.
Citations (16)
View on Semantic Scholar

Summary

No one has generated a summary of this paper yet.

Sign Up to Summarize

Paper to Video (Beta)

No one has generated a video about this paper yet.

Sign Up to Generate All Videos Subscribe on YouTube

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Sign Up to Generate

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Generate Now

Continue Learning

We haven't generated follow-up questions for this paper yet.

Generate Now

Collections

Sign up for free to add this paper to one or more collections.

Sign Up

Tweets

Sign up for free to view the 1 tweet with 1 like about this paper.

Sign Up for Free