Computer Vision Lab
Our Visual Humor (CVPR 2016) datasets can be found here.
Our Visual Question Annswering (VQA) dataset (ICCV 2015) can be found here.
CIDEr (Consensus-based Image Description Evaluation) code as well as the PASCAL-50S and ABSTRACT-50S datasets from our "Consensus-based Image Description Evaluation" paper at CVPR 2015 can be found here.
Datasets and code from our "Zero-Shot Learning via Visual Abstraction" paper at ECCV 2014 can be found here.
Attribute Dominance Dataset: Our dataset containing attribute dominance annotations for face and animal images used in our "Attribute Dominance: What Pops Out?" paper at ICCV 2013.
Spoken Attribute Dataset: Dataset used in our "Spoken Attributes: Mixing Binary and Relative Attributes to Say the Right Thing" paper at ICCV 2013.
Abstract Scenes Dataset: Our dataset containing >10k abstract scenes and coresponding descriptions used in the following two papers:
"Bringing Semantics Into Focus Using Visual Abstraction" paper at CVPR 2013 (Oral).
"Learning the Visual Interpretation of Sentences" paper at ICCV 2013.
Patches Dataset: We provide the patches used in our "The Role of Image Understanding in Contour Detection" paper at CVPR 2012.
Relative Face Attributes Dataset (29 attributes, 60 categories)
Relative Shoes Attributes Dataset (10 attributes, 10 categories)
Part Patch Dataset: A large number of local image patches classified by human subjects in isolation as containing a person's head, torso, arm, hand, leg or foot; and a large number of image windows classified by human subjects in isolation as containing a person or not. The patches and windows come from high-resolution color, gray-scale and normalized gradient images, as well as the low-resolution counterparts of the same.