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W-CODA2024 Track 2 Dataset
Dataset Description
This dataset contains auxiliary data files for the W-CODA (Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving) Track 2 workshop at ECCV 2024. The files provide metadata about the nuScenes validation set for evaluating video generation and detection/segmentation results.
Data Files
nuscenes_infos_temporal_val_3keyframes.pkl- Contains information about key frames from 150 scenes in the nuScenes validation set.
- Each scene has 3 key frames extracted from the first 16 frames.
- Used for evaluating object detection and segmentation performance on the key frames.
- Format: Python pickle file, load with
mmcv.load().
nuscenes_infos_temporal_val_12hz.pkl- Contains metadata for 150 scenes in the nuScenes validation set.
- Provides the first 16 frames (at 12Hz) for each scene.
- Paths to real video frames, used to calculate Fréchet Video Distance (FVD) between generated and real videos.
- Format: Python pickle file, load with
mmcv.load().
data = mmcv.load("./data/nuscenes/nuscenes_infos_temporal_val_3keyframes.pkl")
print(data.keys())
# dict_keys(['infos', 'metadata'])
Dataset Structure
The loaded pickle files contain a list of dictionaries, one per frame, with 'scene_token', 'frame_idx', 'gt_boxes', 'gt_names', 'cams', etc. Their meanings are consistent with the original nus annotations.
Download
Download the files from Hugging Face:
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