Jan 18, 2021 · This paper leverages the divide-and-conquer strategy for rain streak removal by decomposing the learning task into several subproblems.

Feb 6, 2021 · Abstract—Recently an increasing number of algorithms have been proposed for rain streak removal. However, most existing.

Multi-Level Memory Compensation Network for Rain Removal via Divide-and-Conquer Strategy ... multi-scale feature image rain removal algorithm is called MFD.

Multi-Level Memory Compensation Network for Rain Removal via Divide-and-Conquer Strategy(JSTSP2021), Jiang et al. [PDF]; Robust Representation Learning with ...

This paper proposes an image rain removal algorithm based on multi-scale features, which can effectively remove rain streaks.

Divide the overall network into three sub-modules to enhance flexibility. · Feature extraction block is used to extract rain streaks with different directions.

Nov 10, 2023 · In each sub-network, the authors propose a memory compensation module. This module consists of convolutional LSTM and residual connectivity.

Rethinking Lightweight: Multiple Angle Strategy for Efficient ... Multi-Level Memory Compensation Network for Rain Removal via Divide-and-Conquer Strategy.

Multi-Level Memory Compensation Network for Rain Removal via Divide-and-Conquer Strategy ... This paper constructs a novel multi-level memory compensation network ...

This divide-and-conquer scheme to set different objectives for SIFT detection and description leads to good robustness. Compared with state-of-the-art methods, ...