70 citations · 230 across the 33 of their papers we have counts for
7 papers · 1 filter
Generative Adversarial Text to Image Synthesis
Scott Reed, Zeynep Akata, Xinchen Yan +3
Automatic synthesis of realistic images from text would be interesting and useful, but current AI systems are still far from this goal. However, in recent years generic and powerfu…
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…