diff --git a/dataset.html b/dataset.html index 7a8fb01..b4723ae 100644 --- a/dataset.html +++ b/dataset.html @@ -112,22 +112,21 @@
This dataset is used to benchmark the task of Detection and Localization of Instruction Errors, presented in our paper. - You will find the dataset explanation here, as well as the Habitat Integration to use it. + You will find the dataset explanation here, as well as the Habitat integration tools to use it.
Here we show how our json.gz dataset are formed:
+
{"episodes": [
{
- "episode_id": "//integer number",
+ "episode_id": "integer number representing an episode id",
"trajectory_id": "integer number representing the gt trajectory",
"scene_id": "string representing the scene",
"start_position": "list of float representing the start position",
@@ -143,10 +142,10 @@ Val Unseen
"error_type": "integer representing the error type",
"token_swapped": [
{
+ "old_word": "string representing the old word",
"new_word": "string representing the new word",
"token_id" : ["list of bert token id of this word"],
"token_id_position": ["list of integer representing the index of the swapped words in the new instruction"],
- "old_word": "string representing the old word",
}]
}
"old_episode_id": "integer number representing the episode id from which this episode was generated"
@@ -157,7 +156,7 @@ Val Unseen
]}
- In Progress
We reported the scenario depicted in the Fig.1 of the paper (also reported in the Scenario - Section above).
- The videos shows the full trajectories of the agent following the perturbed and correct instructions. +We show the full episode for the example reported in the Scenario + section above (also Fig.1 in the paper).
+ The videos shows the agent following the perturbed and correct instructions respectively.In our paper, we answered the following question: What if we apply IEDL on the R2R-CE +
We answer the following question: What if we apply IEDL on the R2R-CE dataset?
-Our method, IEDL, detected 8 episodes from R2R-CE standard Val Unseen dataset that should be - deleted.
-Here, we report the video showing the trajectories of these particular episodes.
+Our method helped to detect 8 episodes from R2R-CE Val Unseen dataset that present different issues.
+Here we show the BEVBert trajectories for these episodes, as well as the detected issue.
We report also the episode to be removed from the validation split of RxR-CE.
- +Our method helped to detect 10 episodes from RxR-CE Val Unseen dataset that present different issues.
+Here we show the BEVBert trajectories for these episodes, as well as the detected error.
+