| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| - question-answering |
| tags: |
| - Navigation |
| - Retrieval |
| - Visual Embedding |
| - Multimodal |
| - VLM |
| - MLLM |
| size_categories: |
| - n<1K |
| --- |
| |
|
|
| # RAVEN: Long-Horizon Reasoning and Navigation with a Visuo-Spatial-Temporal Memory |
|
|
| [Website](https://#) [Code](https://#) [Citation](#citation) |
|
|
|
|
| Introduction: |
| We release the RAVEN-QA dataset. |
|
|
| - Task: given a subsampled list of frames from a long video, each paired with timestamps and positions, and given a user query, |
| the model or robot will find the time or positions where the queried thing shows up. The query can be objects, places, events, and concepts. |
|
|
| - Categories: They cover dominant and secondary object retrieval (dominant or secondary in view), visual reasoning, commonsense reasoning, information recall, and spatial understanding. |
|
|
| - Diversity: The dataset covers real-world and simulation robot view videos, web-sourced human view videos, and our self-recorded tour videos. |
|
|
| ## Parts |
|
|
| 1. irs: A simple retrieval dataset, including YouTube indoor and outdoor videos. |
| (6 videos; 54 queries; with text and image queries) |
| 2. irs_hard: A harder human-ego retrieval dataset, including self-recorded and web-sourced videos for more challenging object-finding. |
| (3 videos; 41 queries; with text queries) |
| 3. habitat_sim: A robot simulation dataset in Habitat environments. |
| (19 videos; 157 queris; with text queries) |
| 4. real_world: A real-world robot exploration dataset taken in our labs and public areas. |
| (4 videos; 21 queries; with text queries) |
| |
| |
| |
| |
| |
| ## File Structure |
| |
| ``` |
| dataset_name/ |
| ├─ subsplit_name/ |
| │ ├─ video_name/ |
| │ │ ├─ frames/ |
| │ │ │ ├─ frame_001.jpg |
| │ │ │ ├─ frame_002.jpg |
| │ │ │ └─ ... |
| │ │ └─ questions.json |
| │ ├─ ... |
| │ │ |
| ├─ subsplit_name/ |
| │ ├─ video_name/ |
|
|
| ``` |
| |
| |
| |
| ## Citation |
| |
| TODO |
| |
