Shadow Detection With Conditional Generative Adversarial Networks

We introduce scGAN, a novel extension of conditional Generative Adversarial Networks (GAN) tailored for the challenging problem of shadow detection in images. Previous methods for shadow detection focus on learning the local appearance of shadow regions, while using limited local context reasoning in the form of pairwise potentials in a Conditional Random Field... (read more)

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Results from Other Papers


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK SOURCE PAPER COMPARE
RGB Salient Object Detection ISTD scGAN Balanced Error Rate 8.98 # 6
RGB Salient Object Detection SBU scGAN Balanced Error Rate 9.10 # 7
RGB Salient Object Detection UCF scGAN Balanced Error Rate 11.50 # 7

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