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Found 4 papers, 2 papers with code
Human Pose Estimation in Extremely Low-Light Conditions
We study human pose estimation in extremely low-light images.
Combating Label Distribution Shift for Active Domain Adaptation
We consider the problem of active domain adaptation (ADA) to unlabeled target data, of which subset is actively selected and labeled given a budget constraint.
FIFO: Learning Fog-invariant Features for Foggy Scene Segmentation
Robust visual recognition under adverse weather conditions is of great importance in real-world applications.
Ranked #4 on
Domain Adaptation
on Cityscapes-to-FoggyDriving
Style Neophile: Constantly Seeking Novel Styles for Domain Generalization
Existing methods in this direction suppose that a domain can be characterized by styles of its images, and train a network using style-augmented data so that the network is not biased to particular style distributions.
