2.2k citations · 5.2k across the 82 of their papers we have counts for
7 papers · 1 filter
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders
Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha +2
Many approaches in generalized zero-shot learning rely on cross-modal mapping between the image feature space and the class embedding space. As labeled images are expensive, one di…
Grounding Visual Explanations
Lisa Anne Hendricks, Ronghang Hu, Trevor Darrell +1
Existing visual explanation generating agents learn to fluently justify a class prediction. However, they may mention visual attributes which reflect a strong class prior, although…
Manipulating Attributes of Natural Scenes via Hallucination
Levent Karacan, Zeynep Akata, Aykut Erdem +1
In this study, we explore building a two-stage framework for enabling users to directly manipulate high-level attributes of a natural scene. The key to our approach is a deep gener…
Textual Explanations for Self-Driving Vehicles
Jinkyu Kim, Anna Rohrbach, Trevor Darrell +2
Deep neural perception and control networks have become key components of self-driving vehicles. User acceptance is likely to benefit from easy-to-interpret textual explanations wh…
Generating Counterfactual Explanations with Natural Language
Lisa Anne Hendricks, Ronghang Hu, Trevor Darrell +1
Natural language explanations of deep neural network decisions provide an intuitive way for a AI agent to articulate a reasoning process. Current textual explanations learn to disc…
Primal-Dual Wasserstein GAN
Mevlana Gemici, Zeynep Akata, Max Welling
We introduce Primal-Dual Wasserstein GAN, a new learning algorithm for building latent variable models of the data distribution based on the primal and the dual formulations of the…
Multimodal Explanations: Justifying Decisions and Pointing to the Evidence
Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata +4
Deep models that are both effective and explainable are desirable in many settings; prior explainable models have been unimodal, offering either image-based visualization of attent…