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README.md
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- **`pred_visibility`**: Visibility mask for each point [T, N]
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- **`obj_ids`**: Object/cluster IDs for each point [N]
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- **`point_queries`**: Original query point indices [N]
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### 2. Few-shot Split Information (`few_shot_info/`)
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## Point Extraction Details
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### Semantic Point Tracking
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- **Method**: CoTracker3 with semantic clustering on DINOv2 features
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- **Clustering**: Bipartite clustering for semantic entity detection
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## Supported Datasets
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The point tracking data is available for multiple action recognition datasets:
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- **Something Something V2 (SSV2)**
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- **Kinetics**
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- **UCF-101**
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- **HMDB-51**
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## Usage
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- **`pred_visibility`**: Visibility mask for each point [T, N]
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- **`obj_ids`**: Object/cluster IDs for each point [N]
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- **`point_queries`**: Original query point indices [N]
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It also contains **`vid_info`**, which contains the video information of the video the points were extracted:
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- **`fps`**: FPS at which the video was processed for point tracking.
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- **`height`**: Height of the video.
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- **`width`**: Width of the video.
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### 2. Few-shot Split Information (`few_shot_info/`)
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## Point Extraction Details
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Code for extraction can be found on the GitHub repo [here](https://github.com/pulkitkumar95/trokens/tree/main/point_tracking). Some details are provided below.
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### Semantic Point Tracking
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- **Method**: CoTracker3 with semantic clustering on DINOv2 features
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- **Clustering**: Bipartite clustering for semantic entity detection
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## Supported Datasets
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The point tracking data is available for few shot splits of multiple action recognition datasets:
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- **Something Something V2 (SSV2)**
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- **Kinetics**
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- **UCF-101**
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- **HMDB-51**
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- **Finegym**
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## Usage
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