Datasets:
File size: 3,865 Bytes
203f825 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 | {
"meta": {
"benchmark": "STRIDE",
"split": "nuscenes_examples",
"source_dataset": "nuScenes",
"n_questions": 3,
"n_templates": 23,
"n_scenes": 761,
"counts_by_template": {
"SC-6": 50,
"SP-1": 50,
"SP-2": 50,
"SP-3": 50,
"SP-5": 50,
"SP-7": 50,
"SU-1": 50,
"SU-2": 50,
"SU-4": 50,
"SU-7": 50,
"TE-1": 50,
"TE-6": 50,
"TM-2": 50,
"TM-3": 50,
"TM-4": 50,
"TM-5": 50,
"TRJ-1": 50,
"TRJ-2": 50,
"TRJ-3": 50,
"TRJ-4": 50,
"TRJ-5": 50,
"TRJ-6": 50,
"TRJ-7": 50
},
"counts_by_task_family": {
"scene-context": 50,
"space-perception": 250,
"space-understanding": 200,
"time-extrapolation": 100,
"time-memory": 200,
"trajectory-prediction": 350
},
"counts_by_format": {
"OEQ": 350,
"MCQ": 800
},
"notes": [
"Ground-truth answers included for open evaluation.",
"Images are NOT bundled; resolve via formatted_scenes using source_group_file.",
"Open-OEQ ground truths include human-verified revisions."
],
"packaged_at": "2026-09-28T23:42:03.998571+00:00"
},
"tasks": [
{
"choices": {
"A": "Moving toward ego",
"B": "Moving away from ego",
"C": "Moving left-to-right across ego",
"D": "Moving right-to-left across ego",
"E": "Static",
"F": "Same direction as ego"
},
"question": "What is the trajectory direction of the object in the red bounding box in relation to the ego vehicle?",
"task": "space-perception",
"object_id": "abd58e7c79ec435c912afbc2dd93b38e",
"source_group_file": "scene_012/group_002_vehicle_annotations.json",
"id": "SP-1",
"group_id": "group_002",
"object_reference": "the vehicle rear-left at about 38m",
"scene_id": "scene_012",
"ground_truth": "B",
"question_format": "MCQ",
"scoring_type": "mcq"
},
{
"choices": {
"A": "In front",
"B": "Front-right",
"C": "Front-left",
"D": "Left",
"E": "Right",
"F": "Behind"
},
"question": "Where was the object in the red bounding box located relative to the ego vehicle in the previous frame(s)?",
"task": "time-memory",
"object_id": "e1f8fc954ccd4047b257d2fcfad62088",
"source_group_file": "scene_003/group_007_vehicle_annotations.json",
"scene_description": "",
"id": "TM-2",
"group_id": "group_007",
"object_reference": "the vehicle front-right at about 24m",
"scene_id": "scene_003",
"ground_truth": "B",
"question_format": "MCQ",
"scoring_type": "mcq"
},
{
"question": "Describe the overall environment of the scene, including weather, lighting conditions, road type, and notable surrounding activity.",
"task": "scene-context",
"source_group_file": "scene_299/group_001_vehicle_annotations.json",
"scene_description": "Cross bridge, peds, ban, parked bicycle",
"id": "SC-6",
"group_id": "group_001",
"scene_id": "scene_299",
"nuscenes_scene_name": "scene-0299",
"nuscenes_log_location": "boston-seaport",
"ground_truth": "The scene takes place during daytime under partly cloudy conditions with adequate natural lighting. It is set in a straight urban road environment with light to moderate traffic. The road features double yellow lines and crosswalks. Notable surrounding activity includes parked vehicles, industrial buildings (including a 'New Boston Seafood' facility), and some pedestrian activity near sidewalks. There are no visible bridges, barriers, or roundabouts. Traffic flow is steady but not dense.",
"question_format": "OEQ",
"scoring_type": "open_oeq_text"
}
]
}
|