Rain Removal
124 papers with code • 1 benchmarks • 4 datasets
Libraries
Use these libraries to find Rain Removal models and implementationsLatest papers
ViStripformer: A Token-Efficient Transformer for Versatile Video Restoration
Besides, ViStripformer is an effective and efficient transformer architecture with much lower memory usage than the vanilla transformer.
Exploring the potential of channel interactions for image restoration
Image restoration aims to reconstruct a clear image from a degraded observation.
Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge
Diffusion models possess powerful generative capabilities enabling the mapping of noise to data using reverse stochastic differential equations.
Textual Prompt Guided Image Restoration
In this paper, an effective textual prompt guided image restoration model has been proposed.
Prompt-In-Prompt Learning for Universal Image Restoration
Second, we devise a novel prompt-to-prompt interaction module to fuse these two prompts into a universal restoration prompt.
Image Restoration via Frequency Selection
Image restoration aims to reconstruct the latent sharp image from its corrupted counterpart.
TPSeNCE: Towards Artifact-Free Realistic Rain Generation for Deraining and Object Detection in Rain
We first introduce a Triangular Probability Similarity (TPS) constraint to guide the generated images toward clear and rainy images in the discriminator manifold, thereby minimizing artifacts and distortions during rain generation.
See SIFT in a Rain
One is difference of Gaussian (DoG) pyramid recovery network (DPRNet) for SIFT detection, and the other gradients of Gaussian images recovery network (GGIRNet) for SIFT description.
Controlling Vision-Language Models for Multi-Task Image Restoration
In this paper, we present a degradation-aware vision-language model (DA-CLIP) to better transfer pretrained vision-language models to low-level vision tasks as a multi-task framework for image restoration.
EGVD: Event-Guided Video Deraining
In this paper, we approach video deraining by employing an event camera.