Datasets:

IrohXu
/

SocialGesture

@@ -57,3 +57,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text

 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+*.json filter=lfs diff=lfs merge=lfs -text

README.md CHANGED Viewed

@@ -6,7 +6,8 @@ license: cc-by-nc-3.0
 ## Dataset Description
-![](assets/example_gesture.pdf)
 We introduce SocialGesture, the first large-scale dataset specifically designed for multi-person gesture analysis. SocialGesture features a diverse range of natural scenarios and supports multiple gesture analysis tasks, including video-based recognition and temporal localization, providing a valuable resource for advancing the study of gesture during complex social interactions. Furthermore, we propose a novel visual question answering (VQA) task to benchmark vision language models' (VLMs) performance on social gesture understanding. Our findings highlight several limitations of current gesture recognition models, offering insights into future directions for improvement in this field.
@@ -16,7 +17,9 @@ We introduce SocialGesture, the first large-scale dataset specifically designed
 ----videos
     |----xxx.mp4
     |----xxx.mp4
-----vqa_annotation.json
 ```
 ## Reference

 ## Dataset Description
+<img src="assets/gesture_example.png">
 We introduce SocialGesture, the first large-scale dataset specifically designed for multi-person gesture analysis. SocialGesture features a diverse range of natural scenarios and supports multiple gesture analysis tasks, including video-based recognition and temporal localization, providing a valuable resource for advancing the study of gesture during complex social interactions. Furthermore, we propose a novel visual question answering (VQA) task to benchmark vision language models' (VLMs) performance on social gesture understanding. Our findings highlight several limitations of current gesture recognition models, offering insights into future directions for improvement in this field.
 ----videos
     |----xxx.mp4
     |----xxx.mp4
+----train_annotation.json
+----test_annotation.json
+----dataset_stat_link.xlsx
 ```
 ## Reference

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