Add dataset card

README.md

@@ -1,49 +1,11 @@
 ---
 license: other
 license_name: nvidia-evaluation-data-license
-license_link: LICENSE
-tags:
-- video
-- video-understanding
-- benchmark
-- evaluation
-- infrastructure-cameras
-- warehouse
-- smart-city
-- smart-spaces
-configs:
-- config_name: vqa
-  data_files:
-  - split: test
-    path: data/vqa/data_jsons/annotations/*.json
-- config_name: temporal_localization
-  data_files:
-  - split: test
-    path: data/temporal_localization/data_jsons/annotations/*.json
-- config_name: event_verification
-  data_files:
-  - split: test
-    path: data/event_verification/data_jsons/annotations/*.json
-- config_name: referring
-  data_files:
-  - split: test
-    path: data/referring/refdrone_test_llava.json
-- config_name: pointing
-  data_files:
-  - split: test
-    path: data/pointing/VANTAGE_2DPointing.jsonl
-- config_name: tracking
-  data_files:
-  - split: test
-    path: data/tracking/sot_benchmark.jsonl
-- config_name: 2dbbox
-  data_files:
-  - split: test
-    path: data/2dbbox/metadata.jsonl
-- config_name: dense_captioning
-  data_files:
-  - split: test
-    path: data/dense_captioning/metadata.jsonl
+license_link: LICENSE.md
+dataset_info:
+  splits:
+  - name: test
+    num_examples: 35027
 ---
 
 # VANTAGE-BENCH
@@ -98,30 +60,28 @@ VANTAGE-BENCH/
 | Category | Task | Metric |
 |----------|------|--------|
 | Semantic | VQA | Accuracy |
-| Semantic | Event Verification | F1 Score |
+| Semantic | Event Verification | Macro F1 |
 | Temporal | Dense Video Captioning | SODA-c |
-| Temporal | Temporal Localization | mAP@tIoU |
+| Temporal | Temporal Localization | mIoU |
 | Spatial | 2D Object Localization | F1@0.5 |
 | Spatial | 2D Referring Expressions | mIoU |
-| Spatial | 2D Spatial Pointing | Pointing Accuracy |
+| Spatial | 2D Spatial Pointing | Accuracy |
 | Spatio-Temporal | Single Object Tracking | AUC |
 
-Expected submission formats and the leaderboard will be published soon.
+Submit predictions via the [VANTAGE-Bench submission portal](https://vantage-bench.org/submit) and track results on the [official leaderboard](https://huggingface.co/spaces/clemson-computing/VANTAGE-Bench-Leaderboard).
 
 ### Metric Notes
 
 - **Accuracy**: Percentage of correct predictions.
 - **SODA-c**: Metric for dense video captioning quality across event coverage and language quality.
-- **mAP@tIoU**: Mean Average Precision measured over temporal IoU thresholds.
-- **F1 Score**: Harmonic mean of precision and recall.
+- **Macro F1**: Unweighted mean of per-class F1 scores.
 - **F1@0.5**: F1 score at an IoU threshold of 0.5.
-- **mIoU**: Mean Intersection over Union — average overlap between predicted and ground-truth bounding boxes.
-- **Pointing Accuracy**: Percentage of correctly selected target regions.
+- **mIoU**: Mean Intersection over Union — average overlap between predicted and ground-truth regions (spatial bounding boxes or temporal segments, depending on the task).
 - **AUC**: Area under the ROC curve, measuring the model's ability to distinguish correct detections or tracks from incorrect ones across varying confidence thresholds.
 
 ### Evaluation Server
 
-The [VANTAGE-Bench GitHub repository](https://github.com/anon-benchmark/VANTAGE-bench) provides a sample evaluation pipeline for generating model predictions. Predictions are submitted to the official leaderboard, which will go live by the end of May 2026.
+The [VANTAGE-Bench GitHub repository](https://github.com/Clemson-Capstone/VANTAGE-Bench) provides a sample evaluation pipeline for generating model predictions. Predictions are submitted through the [submission portal](https://vantage-bench.org/submit) and scored on the [official leaderboard](https://huggingface.co/spaces/clemson-computing/VANTAGE-Bench-Leaderboard).
 
 ## Dataset Format
 
@@ -177,6 +137,7 @@ Video (mp4) and Images (jpg).
 ## References
 
 - HuggingFace dataset: [nvidia/PhysicalAI-VANTAGE-Bench](https://huggingface.co/datasets/nvidia/PhysicalAI-VANTAGE-Bench)
+- Project website: [vantage-bench.org](https://vantage-bench.org/)
 
 <img src="./assets/vantage_bench_tasks.png" alt="VANTAGE-BENCH task overview across Semantic, Temporal, Spatial, and Spatio-Temporal understanding categories" width="100%">