Snow Removal
9 papers with code • 2 benchmarks • 3 datasets
Snow100K
RVSD
Most implemented papers
Restoring Snow-Degraded Single Images With Wavelet in Vision Transformer
WINS-lab/WiT
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IEEE Access 2023
In our experiments, we evaluated the performance of our model on the popular SRRS, SNOW100K, and CSD datasets, respectively.
Video Rain/Snow Removal by Transformed Online Multiscale Convolutional Sparse Coding
Furthermore, a transformation operator imposed on the background scenes is further embedded into the proposed model, which finely conveys the dynamic background transformations, such as rotations, scalings and distortions, inevitably existed in a real video sequence.
ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-Tree Complex Wavelet Representation and Contradict Channel Loss
weitingchen83/iccv2021-single-image-desnowing-hdcwnet
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ICCV 2021
Moreover, due to the limitation of existing snow datasets, to simulate the snow scenarios comprehensively, we propose a large-scale dataset called Comprehensive Snow Dataset (CSD).
Marine Snow Removal Benchmarking Dataset
This paper introduces a new benchmarking dataset for marine snow removal of underwater images.
LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal
Secondly, we design a Mask Query Transformer (MQFormer) to remove snow with the coarse mask, where we use two parallel encoders and a hybrid decoder to learn extensive snow features under lightweight requirements.
LiSnowNet: Real-time Snow Removal for LiDAR Point Cloud
LiDARs have been widely adopted to modern self-driving vehicles, providing 3D information of the scene and surrounding objects.
Snow Removal for LiDAR Point Clouds with Spatio-temporal Conditional Random Fields
The proposed approach first constructs the CRF based on k-nearest neighbors with the snow confidence derived from the physical priors of snow, such as intensity and distribution.
A deep learning approach for marine snow synthesis and removal
Marine snow, the floating particles in underwater images, severely degrades the visibility and performance of human and machine vision systems.
