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Update README.md

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@@ -49,6 +49,11 @@ Each pickle file contains:
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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/`)
@@ -57,6 +62,8 @@ Data splits for few-shot learning evaluation across multiple datasets.
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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
@@ -80,12 +87,12 @@ Data splits for few-shot learning evaluation across multiple datasets.
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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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- - And others
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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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+
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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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+
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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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