2.2k citations · 5.2k across the 82 of their papers we have counts for
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Feature Generating Networks for Zero-Shot Learning
Yongqin Xian, Tobias Lorenz, Bernt Schiele +1
Suffering from the extreme training data imbalance between seen and unseen classes, most of existing state-of-the-art approaches fail to achieve satisfactory results for the challe…
Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)
Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata +4
Deep models are the defacto standard in visual decision problems due to their impressive performance on a wide array of visual tasks. On the other hand, their opaqueness has led to…
Grounding Visual Explanations (Extended Abstract)
Lisa Anne Hendricks, Ronghang Hu, Trevor Darrell +1
Existing models which generate textual explanations enforce task relevance through a discriminative term loss function, but such mechanisms only weakly constrain mentioned object p…
Zero-Shot Learning -- A Comprehensive Evaluation of the Good, the Bad and the Ugly
Yongqin Xian, Christoph H. Lampert, Bernt Schiele +1
Due to the importance of zero-shot learning, i.e. classifying images where there is a lack of labeled training data, the number of proposed approaches has recently increased steadi…
Channel-Recurrent Autoencoding for Image Modeling
Wenling Shang, Kihyuk Sohn, Yuandong Tian
Despite recent successes in synthesizing faces and bedrooms, existing generative models struggle to capture more complex image types, potentially due to the oversimplification of t…
Zero-Shot Learning -- The Good, the Bad and the Ugly
Yongqin Xian, Bernt Schiele, Zeynep Akata
Due to the importance of zero-shot learning, the number of proposed approaches has increased steadily recently. We argue that it is time to take a step back and to analyze the stat…
Exploiting saliency for object segmentation from image level labels
Seong Joon Oh, Rodrigo Benenson, Anna Khoreva +3
There have been remarkable improvements in the semantic labelling task in the recent years. However, the state of the art methods rely on large-scale pixel-level annotations. This…