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--- |
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annotations_creators: |
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- crowdsourced |
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language_creators: |
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- crowdsourced |
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language: |
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- en |
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license: |
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- other |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 100K<n<1M |
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source_datasets: |
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- original |
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task_categories: |
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- other |
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task_ids: [] |
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paperswithcode_id: something-something |
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pretty_name: Something Something v2 |
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tags: [] |
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--- |
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# Dataset Card for Something Something v2 |
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## Table of Contents |
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- [Table of Contents](#table-of-contents) |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Fields](#data-fields) |
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- [Data Splits](#data-splits) |
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- [Dataset Creation](#dataset-creation) |
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- [Curation Rationale](#curation-rationale) |
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- [Source Data](#source-data) |
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- [Annotations](#annotations) |
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- [Personal and Sensitive Information](#personal-and-sensitive-information) |
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- [Considerations for Using the Data](#considerations-for-using-the-data) |
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- [Social Impact of Dataset](#social-impact-of-dataset) |
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- [Discussion of Biases](#discussion-of-biases) |
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- [Other Known Limitations](#other-known-limitations) |
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- [Additional Information](#additional-information) |
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- [Dataset Curators](#dataset-curators) |
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- [Licensing Information](#licensing-information) |
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- [Citation Information](#citation-information) |
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- [Contributions](#contributions) |
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## Dataset Description |
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- **Homepage:** https://developer.qualcomm.com/software/ai-datasets/something-something |
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- **Repository:** |
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- **Paper:** https://arxiv.org/abs/1706.04261 |
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- **Leaderboard:** https://paperswithcode.com/sota/action-recognition-in-videos-on-something |
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- **Point of Contact:** mailto: [email protected] |
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### Dataset Summary |
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The Something-Something dataset (version 2) is a collection of 220,847 labeled video clips of humans performing pre-defined, basic actions with everyday objects. It is designed to train machine learning models in fine-grained understanding of human hand gestures like putting something into something, turning something upside down and covering something with something. |
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### Supported Tasks and Leaderboards |
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- `action-recognition`: The goal of this task is to classify actions happening in a video. This is a multilabel classification. The leaderboard is available [here](https://paperswithcode.com/sota/action-recognition-in-videos-on-something) |
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### Languages |
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The annotations in the dataset are in English. |
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## Dataset Structure |
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### Data Instances |
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``` |
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{ |
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"video_id": "41775", |
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"video": "<ExFileObject name="">", |
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"text": "moving drawer of night stand", |
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"label": 33, |
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"placeholders": ["drawer", "night stand"]} |
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} |
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``` |
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### Data Fields |
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- `video_id`: `str` Unique identifier for each video. |
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- `video`: `str` File object |
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- `placeholders`: `List[str]` Objects present in the video |
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- `text`: `str` Description of what is happening in the video |
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- `labels`: `int` Action found in the video. Indices from 0 to 173. |
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<details> |
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<summary> |
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Click here to see the full list of Something-Something-v2 class labels mapping: |
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</summary> |
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|0 | Approaching something with your camera | |
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|1 | Attaching something to something | |
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|2 | Bending something so that it deforms | |
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|3 | Bending something until it breaks | |
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|4 | Burying something in something | |
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|5 | Closing something | |
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|6 | Covering something with something | |
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|7 | Digging something out of something | |
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|8 | Dropping something behind something | |
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|9 | Dropping something in front of something | |
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|10 | Dropping something into something | |
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|11 | Dropping something next to something | |
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|12 | Dropping something onto something | |
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|13 | Failing to put something into something because something does not fit | |
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|14 | Folding something | |
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|15 | Hitting something with something | |
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|16 | Holding something | |
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|17 | Holding something behind something | |
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|18 | Holding something in front of something | |
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|19 | Holding something next to something | |
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|20 | Holding something over something | |
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|21 | Laying something on the table on its side, not upright | |
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|22 | Letting something roll along a flat surface | |
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|23 | Letting something roll down a slanted surface | |
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|24 | Letting something roll up a slanted surface, so it rolls back down | |
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|25 | Lifting a surface with something on it but not enough for it to slide down | |
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|26 | Lifting a surface with something on it until it starts sliding down | |
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|27 | Lifting something up completely without letting it drop down | |
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|28 | Lifting something up completely, then letting it drop down | |
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|29 | Lifting something with something on it | |
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|30 | Lifting up one end of something without letting it drop down | |
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|31 | Lifting up one end of something, then letting it drop down | |
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|32 | Moving away from something with your camera | |
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|33 | Moving part of something | |
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|34 | Moving something across a surface until it falls down | |
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|35 | Moving something across a surface without it falling down | |
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|36 | Moving something and something away from each other | |
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|37 | Moving something and something closer to each other | |
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|38 | Moving something and something so they collide with each other | |
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|39 | Moving something and something so they pass each other | |
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|40 | Moving something away from something | |
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|41 | Moving something away from the camera | |
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|42 | Moving something closer to something | |
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|43 | Moving something down | |
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|44 | Moving something towards the camera | |
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|45 | Moving something up | |
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|46 | Opening something | |
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|47 | Picking something up | |
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|48 | Piling something up | |
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|49 | Plugging something into something | |
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|50 | Plugging something into something but pulling it right out as you remove your hand | |
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|51 | Poking a hole into some substance | |
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|52 | Poking a hole into something soft | |
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|53 | Poking a stack of something so the stack collapses | |
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|54 | Poking a stack of something without the stack collapsing | |
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|55 | Poking something so it slightly moves | |
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|56 | Poking something so lightly that it doesn't or almost doesn't move | |
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|57 | Poking something so that it falls over | |
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|58 | Poking something so that it spins around | |
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|59 | Pouring something into something | |
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|60 | Pouring something into something until it overflows | |
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|61 | Pouring something onto something | |
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|62 | Pouring something out of something | |
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|63 | Pretending or failing to wipe something off of something | |
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|64 | Pretending or trying and failing to twist something | |
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|65 | Pretending to be tearing something that is not tearable | |
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|66 | Pretending to close something without actually closing it | |
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|67 | Pretending to open something without actually opening it | |
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|68 | Pretending to pick something up | |
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|69 | Pretending to poke something | |
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|70 | Pretending to pour something out of something, but something is empty | |
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|71 | Pretending to put something behind something | |
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|72 | Pretending to put something into something | |
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|73 | Pretending to put something next to something | |
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|74 | Pretending to put something on a surface | |
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|75 | Pretending to put something onto something | |
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|76 | Pretending to put something underneath something | |
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|77 | Pretending to scoop something up with something | |
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|78 | Pretending to spread air onto something | |
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|79 | Pretending to sprinkle air onto something | |
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|80 | Pretending to squeeze something | |
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|81 | Pretending to take something from somewhere | |
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|82 | Pretending to take something out of something | |
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|83 | Pretending to throw something | |
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|84 | Pretending to turn something upside down | |
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|85 | Pulling something from behind of something | |
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|86 | Pulling something from left to right | |
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|87 | Pulling something from right to left | |
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|88 | Pulling something onto something | |
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|89 | Pulling something out of something | |
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|90 | Pulling two ends of something but nothing happens | |
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|91 | Pulling two ends of something so that it gets stretched | |
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|92 | Pulling two ends of something so that it separates into two pieces | |
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|93 | Pushing something from left to right | |
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|94 | Pushing something from right to left | |
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|95 | Pushing something off of something | |
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|96 | Pushing something onto something | |
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|97 | Pushing something so it spins | |
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|98 | Pushing something so that it almost falls off but doesn't | |
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|99 | Pushing something so that it falls off the table | |
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|100 | Pushing something so that it slightly moves | |
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|101 | Pushing something with something | |
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|102 | Putting number of something onto something | |
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|103 | Putting something and something on the table | |
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|104 | Putting something behind something | |
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|105 | Putting something in front of something | |
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|106 | Putting something into something | |
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|107 | Putting something next to something | |
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|108 | Putting something on a flat surface without letting it roll | |
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|109 | Putting something on a surface | |
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|110 | Putting something on the edge of something so it is not supported and falls down | |
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|111 | Putting something onto a slanted surface but it doesn't glide down | |
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|112 | Putting something onto something | |
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|113 | Putting something onto something else that cannot support it so it falls down | |
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|114 | Putting something similar to other things that are already on the table | |
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|115 | Putting something that can't roll onto a slanted surface, so it slides down | |
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|116 | Putting something that can't roll onto a slanted surface, so it stays where it is | |
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|117 | Putting something that cannot actually stand upright upright on the table, so it falls on its side | |
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|118 | Putting something underneath something | |
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|119 | Putting something upright on the table | |
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|120 | Putting something, something and something on the table | |
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|121 | Removing something, revealing something behind | |
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|122 | Rolling something on a flat surface | |
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|123 | Scooping something up with something | |
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|124 | Showing a photo of something to the camera | |
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|125 | Showing something behind something | |
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|126 | Showing something next to something | |
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|127 | Showing something on top of something | |
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|128 | Showing something to the camera | |
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|129 | Showing that something is empty | |
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|130 | Showing that something is inside something | |
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|131 | Something being deflected from something | |
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|132 | Something colliding with something and both are being deflected | |
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|133 | Something colliding with something and both come to a halt | |
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|134 | Something falling like a feather or paper | |
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|135 | Something falling like a rock | |
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|136 | Spilling something behind something | |
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|137 | Spilling something next to something | |
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|138 | Spilling something onto something | |
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|139 | Spinning something so it continues spinning | |
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|140 | Spinning something that quickly stops spinning | |
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|141 | Spreading something onto something | |
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|142 | Sprinkling something onto something | |
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|143 | Squeezing something | |
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|144 | Stacking number of something | |
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|145 | Stuffing something into something | |
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|146 | Taking one of many similar things on the table | |
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|147 | Taking something from somewhere | |
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|148 | Taking something out of something | |
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|149 | Tearing something into two pieces | |
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|150 | Tearing something just a little bit | |
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|151 | Throwing something | |
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|152 | Throwing something against something | |
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|153 | Throwing something in the air and catching it | |
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|154 | Throwing something in the air and letting it fall | |
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|155 | Throwing something onto a surface | |
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|156 | Tilting something with something on it slightly so it doesn't fall down | |
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|157 | Tilting something with something on it until it falls off | |
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|158 | Tipping something over | |
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|159 | Tipping something with something in it over, so something in it falls out | |
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|160 | Touching (without moving) part of something | |
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|161 | Trying but failing to attach something to something because it doesn't stick | |
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|162 | Trying to bend something unbendable so nothing happens | |
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|163 | Trying to pour something into something, but missing so it spills next to it | |
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|164 | Turning something upside down | |
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|165 | Turning the camera downwards while filming something | |
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|166 | Turning the camera left while filming something | |
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|167 | Turning the camera right while filming something | |
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|168 | Turning the camera upwards while filming something | |
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|169 | Twisting (wringing) something wet until water comes out | |
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|170 | Twisting something | |
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|171 | Uncovering something | |
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|172 | Unfolding something | |
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|173 | Wiping something off of something | |
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</details> |
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### Data Splits |
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| |train |validation| test | |
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|-------------|------:|---------:|------:| |
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|# of examples|168913|24777 |27157 | |
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## Dataset Creation |
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### Curation Rationale |
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From the paper: |
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> Neural networks trained on datasets such as ImageNet have led to major advances |
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in visual object classification. One obstacle that prevents networks from reasoning more |
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deeply about complex scenes and situations, and from integrating visual knowledge with natural language, |
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like humans do, is their lack of common sense knowledge about the physical world. |
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Videos, unlike still images, contain a wealth of detailed information about the physical world. |
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However, most labelled video datasets represent high-level concepts rather than detailed physical aspects |
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about actions and scenes. In this work, we describe our ongoing collection of the |
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“something-something” database of video prediction tasks whose solutions require a common sense |
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understanding of the depicted situation |
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### Source Data |
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#### Initial Data Collection and Normalization |
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From the paper: |
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> As outlined is Section 3 videos available online are largely unsuitable for the goal of learning |
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simple (but finegrained) visual concepts. We therefore ask crowd-workers to provide videos |
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given labels instead of the other way around. |
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#### Who are the source language producers? |
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The dataset authors |
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### Annotations |
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#### Annotation process |
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The label is given first and then the video is collected by an AMT worker. More fine-grained details on the process are in the Section 4 of the work. |
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#### Who are the annotators? |
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AMT workers |
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### Personal and Sensitive Information |
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Nothing specifically discussed in the paper. |
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## Considerations for Using the Data |
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### Social Impact of Dataset |
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The dataset is useful for action recognition pretraining due to diverse set of actions that happen in it. |
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### Discussion of Biases |
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[More Information Needed] |
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### Other Known Limitations |
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[More Information Needed] |
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## Additional Information |
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### Dataset Curators |
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### Licensing Information |
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License is a one-page document as defined by QualComm. Please read the license document in detail before using this dataset [here](https://developer.qualcomm.com/downloads/data-license-agreement-research-use?referrer=node/68935). |
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### Citation Information |
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```bibtex |
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@inproceedings{goyal2017something, |
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title={The" something something" video database for learning and evaluating visual common sense}, |
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author={Goyal, Raghav and Ebrahimi Kahou, Samira and Michalski, Vincent and Materzynska, Joanna and Westphal, Susanne and Kim, Heuna and Haenel, Valentin and Fruend, Ingo and Yianilos, Peter and Mueller-Freitag, Moritz and others}, |
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booktitle={Proceedings of the IEEE international conference on computer vision}, |
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pages={5842--5850}, |
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year={2017} |
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} |
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``` |
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### Contributions |
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Thanks to [@apsdehal](https://github.com/apsdehal) for adding this dataset. |