Name
Abstract | ||
|---|---|---|
We explore blindfold (question-only) baselines for Embodied Question Answering. The EmbodiedQA task requires an agent to answer a question by intelligently navigating in a simulated environment, gathering necessary visual information only through first-person vision before finally answering. Consequently, a blindfold baseline which ignores the environment and visual information is a degenerate solution, yet we show through our experiments on the EQAv1 dataset that a simple question-only baseline achieves state-of-the-art results on the EmbodiedQA task in all cases except when the agent is spawned extremely close to the object. |
Year | Venue | DocType |
|---|---|---|
2018 | arXiv: Computer Vision and Pattern Recognition | Journal |
Volume | Citations | PageRank |
abs/1811.05013 | 1 | 0.35 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ankesh Anand | 1 | 15 | 2.39 |
| Eugene Belilovsky | 2 | 23 | 6.88 |
| kyle kastner | 3 | 68 | 5.24 |
| Hugo Larochelle | 4 | 7692 | 488.99 |
| Aaron C. Courville | 5 | 6671 | 348.46 |