Datasets:
Update README.md
Browse files
README.md
CHANGED
|
@@ -60,8 +60,6 @@ dataset_summary: '
|
|
| 60 |
|
| 61 |
# Dataset Card for Qualcomm Interactive Video Dataset
|
| 62 |
|
| 63 |
-

|
| 64 |
-
|
| 65 |
|
| 66 |
This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 2900 samples.
|
| 67 |
|
|
@@ -89,6 +87,10 @@ session = fo.launch_app(dataset)
|
|
| 89 |
|
| 90 |
### Dataset Description
|
| 91 |
|
|
|
|
|
|
|
|
|
|
|
|
|
| 92 |
QIVD (Qualcomm Interactive Video Dataset) is a comprehensive video question-answering dataset designed for evaluating multimodal AI models on their ability to understand and reason about video content. The dataset contains 2,900 video samples with associated questions, answers, and temporal annotations. Each sample includes a question about the video content, a detailed answer, a short answer, and a timestamp indicating when the answer can be found in the video.
|
| 93 |
|
| 94 |
The dataset covers 13 distinct categories of video understanding tasks, including object referencing, action detection, object attributes, action counting, object counting, and more specialized tasks like audio-visual reasoning and OCR in videos.
|
|
|
|
| 60 |
|
| 61 |
# Dataset Card for Qualcomm Interactive Video Dataset
|
| 62 |
|
|
|
|
|
|
|
| 63 |
|
| 64 |
This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 2900 samples.
|
| 65 |
|
|
|
|
| 87 |
|
| 88 |
### Dataset Description
|
| 89 |
|
| 90 |
+

|
| 91 |
+
|
| 92 |
+
|
| 93 |
+
|
| 94 |
QIVD (Qualcomm Interactive Video Dataset) is a comprehensive video question-answering dataset designed for evaluating multimodal AI models on their ability to understand and reason about video content. The dataset contains 2,900 video samples with associated questions, answers, and temporal annotations. Each sample includes a question about the video content, a detailed answer, a short answer, and a timestamp indicating when the answer can be found in the video.
|
| 95 |
|
| 96 |
The dataset covers 13 distinct categories of video understanding tasks, including object referencing, action detection, object attributes, action counting, object counting, and more specialized tasks like audio-visual reasoning and OCR in videos.
|