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Found 4 papers, 2 papers with code
Ingredient-Oriented Multi-Degradation Learning for Image Restoration
Learning to leverage the relationship among diverse image restoration tasks is quite beneficial for unraveling the intrinsic ingredients behind the degradation.
Visual Recognition-Driven Image Restoration for Multiple Degradation With Intrinsic Semantics Recovery
Deep image recognition models suffer a significant performance drop when applied to low-quality images since they are trained on high-quality images.
Unleashing Potential of Unsupervised Pre-Training With Intra-Identity Regularization for Person Re-Identification
During the pre-training, we attempt to address two critical issues for learning fine-grained ReID features: (1) the augmentations in CL pipeline may distort the discriminative clues in person images.
Unleashing the Potential of Unsupervised Pre-Training with Intra-Identity Regularization for Person Re-Identification
During the pre-training, we attempt to address two critical issues for learning fine-grained ReID features: (1) the augmentations in CL pipeline may distort the discriminative clues in person images.
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