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- Rain Streak Removal via Dual Graph Convolutional Network168
This work proposes a simple yet effective dual graph convolutional network (GCN) for single image rain removal that is easy to implement, end-to-end trainable and computationally efficient and achieves significant improvements over the recent state-of-the-art methods.
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- Efficient Model-Driven Network for Shadow Removal84
This work proposes a new shadow illumination model, which ensures the identity mapping among unshaded regions, and adaptively performs fine grained spatial mapping between shadow regions and their references, and reformulates the shadow removal task as a variational optimization problem.
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- Revisiting Single Image Reflection Removal in the Wild62
An advanced reflection collection pipeline that is highly adaptable to a wide range of real-world reflection scenarios and incurs reduced costs in collecting large-scale aligned reflection pairs is devised, and a reflection location-aware cascaded framework specifically tailored for SIRR is designed.
- Single Image Shadow Detection via Complementary Mechanism50
A novel shadow detection framework by investigating the mutual complementary mechanisms contained in this specific task, which achieves superior shadow detection performance against state-of-the-art methods with a relatively low computational cost.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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