VDADB 2013 - The 1st International Workshop on Visual Domain Adaptation and Dataset Bias

VisDA 2013 solicits original contributions on all topics related to visual dataset bias and visual domain adaptation, with special interests in:
(1) Fundamental studies on visual dataset bias and domain shifts. Physical and statistical characterizations of dataset bias and domain shifts; measuring distribution mismatch and generalization bounds for visual data; visual-prior-guided learning; integration of physical and statistical models.
(2) Novel paradigms accounting for various cross-domain constraints. Feature co-occurrences between domains; semi-supervised and unsupervised adaptations; category and instance level constraints; heterogeneous domains; multiple source domains; transferring unseen categories; negative transfer.
(3) Adapting vision-specific representations and models. Adapting detection, segmentation, reconstruction, and tracking algorithms to new domains; adapting representations of imaging processes, shape and deformations, pictorial structure and graphs, random fields, and visual dynamics to new domains.
(4) Efficient adapting large-scale visual data. Scalable algorithms for adaptation between large datasets, incremental adaptation.
(5) Development of rigorous multi-domain datasets, challenges, and evaluation paradigms.