70 citations · 233 across the 51 of their papers we have counts for
6 papers · 2 filters
Learning Deep Representations of Fine-grained Visual Descriptions
Scott Reed, Zeynep Akata, Bernt Schiele +1
State-of-the-art methods for zero-shot visual recognition formulate learning as a joint embedding problem of images and side information. In these formulations the current best com…
Movie Description
Anna Rohrbach, Atousa Torabi, Marcus Rohrbach +5
Audio Description (AD) provides linguistic descriptions of movies and allows visually impaired people to follow a movie along with their peers. Such descriptions are by design main…
Latent Embeddings for Zero-shot Classification
Yongqin Xian, Zeynep Akata, Gaurav Sharma +3
We present a novel latent embedding model for learning a compatibility function between image and class embeddings, in the context of zero-shot classification. The proposed method…
The Cityscapes Dataset for Semantic Urban Scene Understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos +6
Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications. Object detection has benefited enormously from large-scale datasets, esp…
Multi-Cue Zero-Shot Learning with Strong Supervision
Zeynep Akata, Mateusz Malinowski, Mario Fritz +1
Scaling up visual category recognition to large numbers of classes remains challenging. A promising research direction is zero-shot learning, which does not require any training da…
Generating Visual Explanations
Lisa Anne Hendricks, Zeynep Akata, Marcus Rohrbach +3
Clearly explaining a rationale for a classification decision to an end-user can be as important as the decision itself. Existing approaches for deep visual recognition are generall…