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Datasets:
Yogesh914
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RiskCueBench

Tasks:
Video Classification
Video-Text-to-Text
Modalities:
Text
Formats:
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Languages:
English
Size:
< 1K
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Auto-converted to Parquet Duplicate
video_id
stringlengths
1
3
riskVisualIndicator
stringlengths
3
71
riskSignalDescription
stringlengths
38
203
riskSignalStart
stringclasses
41 values
riskSignalEnd
stringclasses
20 values
accidentStartFrame
stringclasses
21 values
accidentEndFrame
stringclasses
2 values
riskLabel
stringclasses
2 values
11
Traffic light, vehicles ahead, straight-going vehicles
First, the red light turns green; Second, vehicles ahead are waiting, Then the straight-going vehicles are moving at normal speed.
0
29
/
nan
no
14
Right-turn lane vehicles, vehicle ahead
First, vehicles on the right-turn lane are moving at normal speed, then the vehicle ahead has the right turn signal on and is also moving at normal speed.
0
36
/
nan
no
15
Ego car, vehicle ahead, traffic light
During the red light, the ego vehicle is moving normally, while the vehicle ahead has the right turn signal on and is waiting the whole time.
0
29
/
nan
no
18
Waiting vehicles, right intersection vehicles
During the red light, vehicles are waiting, and vehicles going straight from the right intersection are moving at normal speed the whole time.
0
48
/
nan
no
20
Ego car, vehicles on both sides
Ego vehicle is moving at normal speed, while vehicles on both sides are slightly faster for the whole time.
0
29
/
nan
no
21
Ego car, curve
First ego vehicle is turning left on a curve, then moving at normal speed.
0
33
/
nan
no
22
Ego car, lane change
First ego vehicle is changing lanes to the left, then moving at normal speed.
0
33
/
nan
no
23
Vehicle, video shake
The vehicle is moving at normal speed, but the video is shaking significantly the whole time.
0
30
/
nan
no
24
Video shake
The video is shaking significantly the whole time.
0
29
/
nan
no
25
Waiting vehicles, ego car, traffic light
During the red light, vehicles are waiting, and the ego vehicle is slowing down.
0
29
/
nan
no
26
Waiting vehicles, traffic light
During the red light, vehicles are waiting the whole time.
0
38
/
nan
no
27
Traffic light, waiting vehicles, left intersection vehicles
There’s a red light ahead, vehicles are waiting, and vehicles from the left intersection are moving at normal speed the whole time.
0
30
/
nan
no
29
Traffic light, vehicles ahead, ego car
Green light, the vehicles ahead start moving, while the ego vehicle is still waiting.
0
29
/
nan
no
31
Traffic light, ego car
First the red light turns green for a left turn, then ego vehicle is still waiting.
0
43
/
nan
no
33
Ego car, parked vehicles
Ego vehicle is moving normally; at the same time, there are parked vehicles on the right side of the road.
0
38
/
nan
no
34
Ego car, traffic light
During the red light, ego vehicle is waiting the whole time.
0
29
/
nan
no
35
Ego car, traffic light
During the green light, ego vehicle is moving at normal speed the whole time.
0
29
/
nan
no
36
Ego car, traffic light
During the green light, ego vehicle is moving at normal speed the whole time.
0
29
/
nan
no
37
Ego car, right intersection vehicles, traffic light
During the red light, ego vehicle is waiting, then vehicles from the right intersection are moving straight at normal speed.
0
34
/
nan
no
40
Traffic light, ego car
FIrst the red light turns green, then ego vehicle starts moving.
0
29
/
nan
no
44
Ego car, lane change
Ego vehicle is changing to the right lane, moving at normal speed the whole time.
0
29
/
nan
no
45
Ego car, lane change
Ego vehicle is changing to the right lane, moving at normal speed the whole time.
0
32
/
nan
no
47
Stopped vehicle, ego car, lane change
There's a stopped vehicle ahead. First, ego vehicle is moving at normal speed, second it changes lanes to overtake, then returns to the original lane.
0
29
/
nan
no
52
Ego car, turn
After turning, ego vehicle then continues to move at normal speed.
0
38
/
nan
no
56
Ego car, traffic light
During the yellow light, ego vehicle starts slowing down and then stops to wait.
0
32
/
nan
no
64
Ego car
Ego vehicle is waiting the whole time.
0
30
/
nan
no
65
Ego car, parking space
First, ego vehicle exits a parking space on the left then it continues at normal speed.
0
45
/
nan
no
67
Vehicle ahead, ego car, right vehicle, traffic light
During the green light, the vehicle ahead turns left, while the ego car and the vehicle on the right go straight at normal speed.
0
29
/
nan
no
71
Ego car, side intersection vehicles, traffic light
During the red light, ego vehicle waits while traffic at both side intersections moves normally.
0
31
/
nan
no
73
Ego car, white car
FIrst, ego vehicle is moving at normal speed; then a white car on the right changes lanes and overtakes slightly faster.
0
44
/
nan
no
74
Ego car
Ego vehicle going straight moves at normal speed the whole time.
0
30
/
nan
no
75
Ego car, curve
EGo vehicle going straight moves at normal speed then enters a curve.
0
36
/
nan
no
76
Ego car, left-side vehicle, traffic light
During the green light, ego vehicle moves at normal speed; at the same time, the vehicle on the left is slightly faster.
0
45
/
nan
no
77
Ego car, lane change
Ego vehicle changes lanes to the left, then continues at normal speed.
0
33
/
nan
no
79
Ego car, right intersection vehicles, traffic light
During the red light, ego vehicle waits while vehicles at the right intersection go straight at normal speed.
0
43
/
nan
no
81
Ego car
Ego vehicle going straight moves at normal speed the whole time.
0
32
/
nan
no
83
Ego car, traffic light
During the green light, ego vehicle moves at normal speed and then brakes to wait after a short distance.
0
33
/
nan
no
86
Vehicle ahead, ego car, traffic light
During the yellow light, the vehicle ahead passes quickly while the ego vehicle slows down to wait.
0
32
/
nan
no
88
Ego car, traffic light
During the red light, ego vehicle is parked on the road the whole time.
0
32
/
nan
no
89
Ego car, traffic light
During the green light, ego vehicle is parked on the road the whole time.
0
31
/
nan
no
91
Ego car
Ego vehicle is moving at normal speed the whole time.
0
29
/
nan
no
97
Ego car, traffic light
During the red light, ego vehicle waits the whole time.
0
34
/
nan
no
102
Ego car
Ego vehicle moves slowly, then preparing to turn left.
0
44
/
nan
no
103
Vehicle ahead, ego car
The vehicle ahead is being washed; then the ego vehicle slowly moves forward to the washing spot.
0
33
/
nan
no
105
Ego car
Ego vehicle is being washed the whole time.
0
48
/
nan
no
106
Ego car, traffic light
During the green light, ego vehicle slowly enters the waiting area.
0
29
/
nan
no
107
Ego car
Ego vehicle slowly enters the waiting area and then waits.
0
29
/
nan
no
108
Ego car, oncoming traffic
The ego vehicle begins to move slowly on the road, while oncoming traffic moves normally.
0
33
/
nan
no
110
Vehicle, ego car, u-turn
The vehicle proceeds straight normally; the ego vehicle then makes a u-turn
0
29
/
nan
no
111
Vehicles, ego car, traffic light
During the red light, all vehicle waits and the ego vehicle decelerates.
0
43
/
nan
no
113
Vehicle ahead, right-side vehicle, oncoming car, ego car, traffic light
During the red light, vehicle ahead moves normally; first a vehicle on the right exits a parking spot; an oncoming car signals a left turn and waits; the ego car proceeds to the intersection then waits.
0
29
/
nan
no
114
Vehicle in front, oncoming traffic, ego car, traffic light
During the red light, vehicle waits; first the vehicle in front of the ego car angles left; oncoming traffic arrives at the intersection then waits.
0
35
/
nan
no
122
Oncoming traffic, traffic light, ego car
Oncoming traffic moves normally; first, the light changes from green to red; the ego car reaches the intersection and then waits.
0
36
/
nan
no
123
Ego car, traffic light, side intersection vehicles, black car
During the red light, ego vehicle waits; at the same time side intersections have normal traffic flow; a black car turns left at the left-side intersection.
0
38
/
nan
no
126
Ego car, traffic light
During the green light, ego vehicle moves at normal speed the whole time.
0
32
/
nan
no
131
Vehicle ahead, ego car, oncoming traffic
vehicle ahead moves slowly and then brakes; the ego car brakes suddenly; oncoming traffic moves normally.
0
29
/
nan
no
133
Ego car, oncoming traffic, right-side turning car
The ego car proceeds straight; oncoming traffic moves straight at normal speed; then a car turns right from the right intersection.
0
34
/
nan
no
136
Ego car, traffic light, stop line
During the red light, ego vehicle first drives to the stop line, then waits; later, the light turns green.
0
43
/
nan
no
137
Ego car, traffic light
During the green light, ego vehicle first turns right, then left.
0
29
/
nan
no
138
Ego car
Ego vehicle moves slowly the whole time.
0
30
/
nan
no
139
Ego car
Ego vehicle moves slowly the whole time.
0
29
/
nan
no
142
Ego car, traffic light
During the green light, ego vehicle begins to move slowly.
0
36
/
nan
no
146
Vehicle ahead, ego car
The vehicle ahead signals a left turn; at the same time ego vehicle waits.
0
39
/
nan
no
147
Vehicle ahead, ego car
The vehicle ahead signals a left turn and moves forward slightly; at the same time ego vehicle waits.
0
29
/
nan
no
148
Ego car, right-side vehicle
Ego vehicle moves at normal speed; at the same time the vehicle on the right is slightly faster.
0
33
/
nan
no
154
Ego car
Ego vehicle proceeds straight at normal speed the whole time.
0
30
/
nan
no
155
Ego car
EGo vehicle proceeds straight at normal speed the whole time.
0
43
/
nan
no
156
Ego car
Ego vehicle proceeds straight at normal speed the whole time.
0
31
/
nan
no
157
Ego car, lane change, vehicle ahead
During the green light, the ego car first changes lanes to the right; then the vehicle ahead also signals a right turn.
0
42
/
nan
no
160
Ego car
Ego vehicle is waiting the whole time.
0
34
/
nan
no
161
Ego car, left-side traffic
Ego vehicle is waiting, at the same time traffic on the left side is moving normally.
0
42
/
nan
no
162
Ego car, left-side traffic
Ego vehicle is waiting, at the same time traffic on the left side is moving normally.
0
32
/
nan
no
165
Ego car, left-side traffic
Ego vehicle is waiting, at the same time traffic on the left side is moving normally.
0
29
/
nan
no
166
Vehicle
The vehicle first wait then starts to move slowly.
0
40
/
nan
no
167
Vehicle
The vehicle first wait then starts to move slowly.
0
29
/
nan
no
168
Vehicle
The vehicle first wait then starts to move slowly.
0
29
/
nan
no
170
Vehicle ahead, ego car
The vehicle ahead signals a right turn, at the same time ego vehicle is waiting.
0
44
/
nan
no
173
Ego car
Ego vehicle is moving at normal speed the whole time.
0
34
/
nan
no
179
Ego car
Ego vehicle is moving at normal speed the whole time.
0
41
/
nan
no
180
Ego car, traffic light
During the green light, ego vehicle moves at normal speed the whole time.
0
37
/
nan
no
182
Ego car, vehicle ahead
Ego vehicle is moving normally, while the vehicle ahead is turning right.
0
33
/
nan
no
183
Traffic light, left-side vehicle
The green light turns yellow, then the vehicle on the left turns left.
0
47
/
nan
no
184
Vehicle ahead, ego car, right-side vehicle
The vehicle ahead first signals a left turn and starts moving; the ego vehicle then waits; at the same time the vehicle on the right moves normally.
0
41
/
nan
no
186
Vehicle ahead, traffic light
During the red light, the vehicle ahead first signals a left turn then waits.
0
39
/
nan
no
187
Vehicle, oncoming vehicle, traffic light
During the green light, the vehicle moves at normal speed; at the same time an oncoming vehicle is turning left.
0
37
/
nan
no
189
Ego car, traffic light
During the red light, the ego car turns right.
0
37
/
nan
no
191
Vehicle, left-side vehicle
The vehicle moves at normal speed; then the vehicle on the left changes lanes to the right.
0
29
/
nan
no
192
Vehicle
The vehicle moves at normal speed the whole time.
0
29
/
nan
no
194
Ego car
Ego vehicle is waiting the whole time.
0
29
/
nan
no
195
Ego car
Ego vehicle is waiting the whole time.
0
29
/
nan
no
196
Vehicles
All vehicle moves straight at normal speed the whole time.
0
36
/
nan
no
198
Vehicles
All vehicle moves slowly the whole time.
0
29
/
nan
no
201
Vehicle, traffic light
During the green light, the vehicle turns left.
0
40
/
nan
no
203
Vehicles, intersection
First, all vehicle moves at normal speed, then stops at the intersection.
0
36
/
nan
no
206
Vehicles, right turn
All vehicle turns right at normal speed the whole time.
0
48
/
nan
no
207
Vehicles, right turn
All vehicle turns right at normal speed the whole time.
0
40
/
nan
no
208
Vehicles, straight movement
All vehicle moves straight at normal speed the whole time.
0
36
/
nan
no
209
Vehicle, stop line, traffic light, right intersection
During the red light, the vehicle first moves to the stop line then waits; the intersection on the right has normal traffic flow.
0
45
/
nan
no
210
Vehicle, traffic light
During the red light, the vehicle waits the whole time.
0
33
/
nan
no
218
Vehicles, video shake
All vehicle is waiting; the camera shakes.
0
35
/
nan
no
End of preview. Expand in Data Studio

🚨 RiskCueBench

A benchmark dataset for evaluating risk reasoning capabilities in video understanding models

Dataset on HF

📖 Overview

RiskCueBench provides fine-grained annotations of risk signals—visual cues that precede potentially dangerous events. This dataset contains annotated video clips from two domains: 🚗 traffic accidents and 📢 protest events, designed to test temporal risk anticipation and visual reasoning.

✨ Key Features

Feature Description
🎯 Risk Signal Annotations Temporal boundaries marking when risk indicators appear
📝 Rich Descriptions Detailed narratives of visual cues and event progressions
🏷️ Binary Labels Clear yes/no labels for whether risk materializes
🌐 Cross-domain Two distinct domains for generalization testing

🎓 Evaluation Tasks

The dataset enables evaluation of models on:

  • 🔍 Risk Signal Detection — Identifying visual cues that indicate potential danger
  • ⏱️ Temporal Reasoning — Understanding the progression from risk signals to outcomes
  • 🔄 Cross-domain Generalization — Testing on both traffic and social scenarios

📊 Dataset Statistics

Split Domain Samples Description
carcrash 🚗 Traffic 502 Dashcam footage of driving scenarios
protest 📢 Social Events 484 Protest and crowd footage

📥 Downloading the Videos

🚗 Car Crash Videos

The car crash videos are sourced from the Car Crash Dataset (CCD) published in ACM MM 2020.

To download:

  1. 🔗 Visit the official repository: CarCrashDataset
  2. 📦 Download the dataset from Google Drive (link provided in the repository)
  3. 🔢 The video_id column corresponds to the video filenames in the Crash-1500 and Normal folders
📚 Citation for CCD 
@InProceedings{BaoMM2020,
    author = {Bao, Wentao and Yu, Qi and Kong, Yu},
    title  = {Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning},
    booktitle = {ACM Multimedia Conference},
    year   = {2020}
}

📢 Protest Videos

The protest videos are sourced from YouTube. The video_id column contains the YouTube video ID.

URL Format:

https://www.youtube.com/watch?v={video_id}

Example: For video_id = "5gM1gnMkUKU" → https://www.youtube.com/watch?v=5gM1gnMkUKU

💡 Tip: Use tools like yt-dlp or pytube to download videos programmatically.

📋 Column Descriptions

Column Type Description
video_id str 🎬 Unique identifier for the video. For car crash: filename ID from CCD. For protest: YouTube video ID.
riskVisualIndicator str 👁️ Concise description of visual cues that signal potential risk
riskSignalDescription str 📝 Detailed narrative of what happens during the risk signal period
riskSignalStart str ⏱️ Frame marking the beginning of the risk signal
riskSignalEnd str ⏱️ Frame marking the end of the risk signal
accidentStartFrame str 💥 Frame when incident begins ("/" = no incident)
accidentEndFrame str 🏁 Frame when incident ends
riskLabel str 🏷️ "yes" = risk materializes, "no" = remains safe

💻 Usage Example 

from datasets import load_dataset

# 📦 Load the full dataset
dataset = load_dataset("Yogesh914/RiskCueBench")

# 🔀 Access specific splits
carcrash_data = dataset["carcrash"]
protest_data = dataset["protest"]

# 🎯 Filter for risky scenarios
risky_carcrash = carcrash_data.filter(lambda x: x["riskLabel"] == "yes")
risky_protest = protest_data.filter(lambda x: x["riskLabel"] == "yes")

# 📄 Access a sample
sample = carcrash_data[0]
print(f"Video ID: {sample['video_id']}")
print(f"Risk Signal: {sample['riskSignalDescription']}")
print(f"Risk Label: {sample['riskLabel']}")

📝 Data Samples

🚗 Car Crash Example (Risk = ✅ Yes) 

video_id: 1
riskVisualIndicator: "Black car, intersection"
riskSignalDescription: "First, a black-colored car enters the intersection against 
                        the traffic, then it continues into the driver's path."
riskSignalStart: 23        # frame number
riskSignalEnd: 31          # frame number
accidentStartFrame: 32     # frame number
accidentEndFrame: 50
riskLabel: "yes"

📢 Protest Example (Risk = ❌ No) 

video_id: "5gM1gnMkUKU"
riskVisualIndicator: "Police body language, repeated hand gesture"
riskSignalDescription: "First a group of geared police show up, then one police 
                        use subtle body language to express message seem to be 
                        'come here', and did it twice."
riskSignalStart: "00:00"   # MM:SS format
riskSignalEnd: "00:13"     # MM:SS format
accidentStartFrame: "/"    # no incident
accidentEndFrame: "/"
riskLabel: "no"

📢 Protest Example (Risk = ✅ Yes) 

video_id: "m6CwOP4rUAo"
riskVisualIndicator: "Police tank appears, gun raised, aiming gesture"
riskSignalDescription: "First a few police on police tank show up, then the 
                        police tank raise gun up and target at the protestors"
riskSignalStart: "00:17"   # MM:SS format
riskSignalEnd: "00:18"     # MM:SS format
accidentStartFrame: "00:19"
accidentEndFrame: "00:25"
riskLabel: "yes"

📜 License

Dataset License
🚗 Car Crash (CCD) MIT License — Original Repo
📢 Protest Videos Subject to YouTube Terms of Service

📚 Citation

If you use this dataset, please cite:

@dataset{riskcuebench2025,
    title = {RiskCueBench: A Benchmark for Video Risk Reasoning},
    author = {[Authors]},
    year = {2025},
    publisher = {},
    url = {https://huggingface.co/datasets/Yogesh914/RiskCueBench}
}

Additionally, please cite the Car Crash Dataset if you use the carcrash split:

@InProceedings{BaoMM2020,
    author = {Bao, Wentao and Yu, Qi and Kong, Yu},
    title  = {Uncertainty-based Traffic Accident Anticipation with Spatio-Temporal Relational Learning},
    booktitle = {ACM Multimedia Conference},
    year   = {2020}
}

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