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Found 4 papers, 1 papers with code
Intrinsic Decomposition of Document Images In-the-Wild
However, document shadow or shading removal results still suffer because: (a) prior methods rely on uniformity of local color statistics, which limit their application on real-scenarios with complex document shapes and textures and; (b) synthetic or hybrid datasets with non-realistic, simulated lighting conditions are used to train the models.
Bag of Negatives for Siamese Architectures
Training a Siamese architecture for re-identification with a large number of identities is a challenging task due to the difficulty of finding relevant negative samples efficiently.
Deep intrinsic decomposition trained on surreal scenes yet with realistic light effects
Estimation of intrinsic images still remains a challenging task due to weaknesses of ground-truth datasets, which either are too small or present non-realistic issues.
Light Direction and Color Estimation from Single Image with Deep Regression
We present a method to estimate the direction and color of the scene light source from a single image.
