Raindrop Removal

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

2 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

12 shown of 12 papers with code (22 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Attentive Generative Adversarial Network for Raindrop Removal from a Single Image
  28 Nov 2017 3 repositories listed Syntology ran 4 of 5 samples · 1 unverified · 2 pointer-only (licence)
  This injection of visual attention to both generative and discriminative networks is the main contribution of this paper.
• Unsupervised Raindrop Removal from a Single Image using Conditional Diffusion Models
  13 May 2025 1 repository listed
  Raindrop removal is a challenging task in image processing.
• Image Restoration via Multi-domain Learning
  7 May 2025 1 repository listed
  Due to adverse atmospheric and imaging conditions, natural images suffer from various degradation phenomena.
• NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
  17 Apr 2025 1 repository listed
  This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images.
• Learning Truncated Causal History Model for Video Restoration
  4 Oct 2024 1 repository listed Syntology ran 7 of 12 samples · 5 unverified
  In this work, we propose TURTLE to learn the truncated causal history model for efficient and high-performing video restoration.
• Raindrop Clarity: A Dual-Focused Dataset for Day and Night Raindrop Removal
  24 Jul 2024 1 repository listed Syntology ran 3 of 4 samples · 1 unverified · 3 pointer-only (licence)
  There are 5, 442 daytime raindrop images and 9, 744 nighttime raindrop images.
• UAV-Rain1k: A Benchmark for Raindrop Removal from UAV Aerial Imagery
  8 Feb 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Raindrops adhering to the lens of UAVs can obstruct visibility of the background scene and degrade image quality.
• Adapt or Perish: Adaptive Sparse Transformer with Attentive Feature Refinement for Image Restoration
  1 Jan 2024 1 repository listed
  Meanwhile FRFN employs an enhance-and-ease scheme to eliminate feature redundancy in channels enhancing the restoration of clear latent images.
• WaveDM: Wavelet-Based Diffusion Models for Image Restoration
  23 May 2023 1 repository listed
  Latest diffusion-based methods for many image restoration tasks outperform traditional models, but they encounter the long-time inference problem.
• Video Waterdrop Removal via Spatio-Temporal Fusion in Driving Scenes
  12 Feb 2023 1 repository listed
  The waterdrops on windshields during driving can cause severe visual obstructions, which may lead to car accidents.
• Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models
  29 Jul 2022 1 repository listed Syntology ran 10 of 11 samples · 1 unverified
  Image restoration under adverse weather conditions has been of significant interest for various computer vision applications.
• Removing Raindrops and Rain Streaks in One Go
  19 Jun 2021 1 repository listed
  First, we propose a complementary cascaded network architecture, namely CCN, to remove rain streaks and raindrops in a unified framework.

Syntology lines on 5 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.