id
int64 73
52.5k
| gender
stringclasses 3
values | race
stringclasses 5
values | lang
stringclasses 52
values | age
stringclasses 10
values | filesize
float64 2.7
1.59k
| width
int64 608
3.84k
| height
int64 720
2.16k
| length
float64 9.2
179
| fps
float64 10
60
|
|---|---|---|---|---|---|---|---|---|---|
51,392
|
female
|
white
|
el
|
30-39
| 18.4
| 1,920
| 1,080
| 51.12
| 25
|
51,393
|
female
|
white
|
el
|
30-39
| 35.9
| 1,920
| 1,080
| 97.64
| 25
|
51,394
|
female
|
white
|
el
|
30-39
| 11.4
| 1,920
| 1,080
| 31.88
| 25
|
51,395
|
female
|
white
|
el
|
30-39
| 13.5
| 1,920
| 1,080
| 36.4
| 25
|
51,396
|
female
|
white
|
el
|
30-39
| 33.8
| 1,920
| 1,080
| 88.12
| 25
|
51,397
|
female
|
white
|
el
|
30-39
| 42.6
| 1,920
| 1,080
| 106
| 25
|
51,398
|
female
|
white
|
el
|
30-39
| 17.4
| 1,920
| 1,080
| 44.52
| 25
|
51,399
|
female
|
white
|
el
|
30-39
| 44
| 1,920
| 1,080
| 117.96
| 25
|
51,400
|
female
|
white
|
el
|
30-39
| 27.9
| 1,920
| 1,080
| 68.32
| 25
|
51,401
|
female
|
white
|
el
|
30-39
| 28.2
| 1,920
| 1,080
| 80.56
| 25
|
51,402
|
female
|
white
|
el
|
30-39
| 13
| 1,920
| 1,080
| 37.44
| 25
|
51,403
|
female
|
white
|
el
|
20-29
| 117.5
| 1,920
| 1,080
| 106.67
| 30
|
51,404
|
female
|
white
|
el
|
20-29
| 44.3
| 1,920
| 1,080
| 47.73
| 30
|
51,405
|
female
|
asian
|
el
|
20-29
| 48.1
| 1,920
| 1,080
| 74.06
| 50
|
51,406
|
female
|
asian
|
el
|
20-29
| 24
| 1,920
| 1,080
| 36.28
| 50
|
51,407
|
female
|
asian
|
el
|
20-29
| 101.6
| 1,920
| 1,080
| 154.64
| 50
|
51,408
|
female
|
asian
|
el
|
20-29
| 99.6
| 1,920
| 1,080
| 170.88
| 50
|
51,409
|
female
|
asian
|
el
|
20-29
| 22.1
| 1,920
| 1,080
| 39.68
| 50
|
51,410
|
male
|
white
|
el
|
40-49
| 96.7
| 3,840
| 2,160
| 82.62
| 60
|
51,411
|
male
|
white
|
el
|
40-49
| 145.7
| 3,840
| 2,160
| 127.02
| 60
|
51,412
|
female
|
white
|
el
|
30-39
| 102.7
| 1,920
| 1,080
| 159.36
| 30
|
51,413
|
female
|
white
|
el
|
30-39
| 99.2
| 1,920
| 1,080
| 156.12
| 30
|
51,414
|
female
|
white
|
el
|
30-39
| 55.2
| 1,920
| 1,080
| 82.48
| 30
|
51,415
|
female
|
white
|
el
|
30-39
| 101.5
| 1,920
| 1,080
| 140.84
| 30
|
51,416
|
female
|
white
|
el
|
30-39
| 24.1
| 1,920
| 1,080
| 31.83
| 30
|
51,417
|
male
|
white
|
el
|
30-39
| 27.3
| 1,920
| 1,080
| 103.1
| 60
|
51,418
|
male
|
white
|
el
|
30-39
| 12
| 1,920
| 1,080
| 45.68
| 60
|
51,419
|
male
|
white
|
el
|
30-39
| 9.6
| 1,920
| 1,080
| 41.78
| 30
|
51,420
|
male
|
white
|
el
|
30-39
| 12.6
| 1,920
| 1,080
| 61.93
| 30
|
51,421
|
male
|
white
|
el
|
30-39
| 8.7
| 1,920
| 1,080
| 37.5
| 30
|
51,422
|
male
|
white
|
el
|
30-39
| 12.8
| 1,920
| 1,080
| 55.76
| 30
|
51,423
|
male
|
white
|
el
|
30-39
| 10.7
| 1,920
| 1,080
| 50.55
| 30
|
51,424
|
male
|
white
|
el
|
30-39
| 17.6
| 1,920
| 1,080
| 80.38
| 30
|
51,425
|
male
|
white
|
el
|
30-39
| 9.9
| 1,920
| 1,080
| 46.75
| 30
|
51,426
|
female
|
white
|
el
|
20-29
| 15.2
| 1,920
| 1,080
| 30.93
| 30
|
51,427
|
male
|
white
|
el
|
30-39
| 107.2
| 1,920
| 1,080
| 177.48
| 30
|
51,428
|
female
|
white
|
el
|
30-39
| 38.5
| 1,920
| 1,080
| 44.02
| 60
|
51,429
|
female
|
white
|
el
|
30-39
| 42.6
| 1,920
| 1,080
| 48.55
| 60
|
51,430
|
female
|
white
|
el
|
30-39
| 27.3
| 1,920
| 1,080
| 32.22
| 60
|
51,431
|
female
|
white
|
el
|
30-39
| 70.7
| 1,920
| 1,080
| 84.53
| 60
|
51,432
|
female
|
white
|
el
|
30-39
| 37
| 1,920
| 1,080
| 46.35
| 60
|
51,433
|
female
|
white
|
el
|
30-39
| 34.8
| 1,920
| 1,080
| 39.5
| 60
|
51,434
|
female
|
white
|
el
|
30-39
| 25.9
| 1,920
| 1,080
| 30.1
| 60
|
51,435
|
female
|
white
|
el
|
30-39
| 27.4
| 1,920
| 1,080
| 32.22
| 60
|
51,436
|
female
|
asian
|
en
|
20-29
| 15.9
| 1,920
| 1,080
| 41.24
| 25
|
51,437
|
female
|
asian
|
en
|
20-29
| 16.7
| 1,920
| 1,080
| 40.76
| 25
|
51,438
|
female
|
white
|
el
|
20-29
| 21.5
| 1,908
| 1,080
| 59.52
| 60
|
51,439
|
female
|
white
|
el
|
20-29
| 22.7
| 1,908
| 1,080
| 58.45
| 60
|
51,440
|
female
|
white
|
el
|
20-29
| 23.9
| 1,908
| 1,080
| 59.9
| 60
|
51,441
|
female
|
white
|
el
|
20-29
| 18.5
| 1,908
| 1,080
| 46.92
| 60
|
51,442
|
male
|
white
|
el
|
20-29
| 62.7
| 1,920
| 1,080
| 154.92
| 30
|
51,443
|
male
|
white
|
el
|
20-29
| 23.2
| 1,920
| 1,080
| 47.65
| 30
|
51,444
|
female
|
white
|
el
|
40-49
| 30.5
| 1,920
| 1,080
| 30.93
| 30
|
51,445
|
female
|
white
|
sw
|
20-29
| 36.3
| 1,920
| 1,080
| 101.5
| 30
|
51,446
|
female
|
white
|
el
|
20-29
| 22.1
| 1,920
| 1,080
| 33.08
| 25
|
51,447
|
female
|
white
|
el
|
20-29
| 33
| 1,920
| 1,080
| 51.65
| 30
|
51,448
|
female
|
white
|
el
|
20-29
| 36
| 1,920
| 1,080
| 50.35
| 30
|
51,449
|
female
|
white
|
el
|
20-29
| 44.6
| 1,920
| 1,080
| 63.96
| 25
|
51,450
|
male
|
white
|
el
|
60-69
| 78.8
| 3,840
| 2,160
| 35.44
| 30
|
51,451
|
male
|
white
|
el
|
60-69
| 101.4
| 3,840
| 2,160
| 45.05
| 30
|
51,452
|
male
|
white
|
el
|
60-69
| 96.7
| 3,840
| 2,160
| 43.34
| 30
|
51,453
|
male
|
white
|
el
|
60-69
| 71.2
| 3,840
| 2,160
| 31.23
| 30
|
51,454
|
male
|
white
|
el
|
60-69
| 75.7
| 3,840
| 2,160
| 34.33
| 30
|
51,455
|
male
|
white
|
en
|
20-29
| 49.3
| 3,840
| 2,160
| 41.42
| 24
|
51,456
|
female
|
white
|
el
|
20-29
| 22.5
| 1,920
| 1,080
| 35.7
| 30
|
51,457
|
female
|
white
|
el
|
20-29
| 46.3
| 1,920
| 1,080
| 89.26
| 30
|
51,458
|
female
|
white
|
el
|
20-29
| 85.6
| 1,920
| 1,080
| 172.34
| 30
|
51,459
|
female
|
white
|
el
|
20-29
| 88.5
| 1,920
| 1,080
| 178.51
| 30
|
51,460
|
female
|
white
|
el
|
20-29
| 33.6
| 1,920
| 1,080
| 63.63
| 30
|
51,461
|
female
|
white
|
el
|
20-29
| 51.5
| 1,920
| 1,080
| 155.66
| 24
|
51,462
|
female
|
white
|
el
|
20-29
| 59.7
| 1,920
| 1,080
| 167.54
| 24
|
51,463
|
female
|
white
|
el
|
20-29
| 24
| 1,920
| 1,080
| 68.69
| 24
|
51,464
|
male
|
white
|
el
|
20-29
| 19.6
| 1,920
| 1,080
| 50.52
| 25
|
51,465
|
male
|
white
|
el
|
20-29
| 13.4
| 1,920
| 1,080
| 37.64
| 25
|
51,466
|
female
|
asian
|
el
|
30-39
| 39.1
| 1,920
| 1,080
| 31.83
| 30
|
51,467
|
female
|
white
|
el
|
20-29
| 25.9
| 1,920
| 1,080
| 53.36
| 25
|
51,468
|
female
|
white
|
el
|
20-29
| 10.8
| 1,920
| 1,080
| 30.2
| 25
|
51,469
|
female
|
white
|
el
|
20-29
| 14.1
| 1,920
| 1,080
| 35.28
| 25
|
51,470
|
female
|
white
|
el
|
20-29
| 40.6
| 1,920
| 1,080
| 89.96
| 25
|
51,471
|
female
|
white
|
el
|
20-29
| 16.7
| 1,920
| 1,080
| 39.72
| 25
|
51,472
|
female
|
white
|
el
|
20-29
| 27.5
| 1,920
| 1,080
| 61.8
| 25
|
51,473
|
female
|
white
|
el
|
20-29
| 20.6
| 1,920
| 1,080
| 50.93
| 30
|
51,474
|
female
|
white
|
el
|
20-29
| 52.2
| 1,920
| 1,080
| 117.03
| 30
|
51,475
|
female
|
white
|
el
|
20-29
| 15.8
| 1,920
| 1,080
| 35.67
| 60
|
51,476
|
male
|
white
|
en
|
30-39
| 56
| 3,840
| 2,160
| 34.68
| 25
|
51,477
|
female
|
white
|
el
|
20-29
| 14
| 1,920
| 1,080
| 37.5
| 24
|
51,478
|
female
|
white
|
el
|
20-29
| 20.3
| 1,920
| 1,080
| 57.6
| 24
|
51,479
|
female
|
white
|
el
|
20-29
| 24.7
| 1,920
| 1,080
| 74.91
| 24
|
51,480
|
female
|
white
|
el
|
20-29
| 14.7
| 1,920
| 1,080
| 37.66
| 24
|
51,481
|
female
|
white
|
el
|
20-29
| 13.3
| 1,920
| 1,080
| 33.53
| 24
|
51,482
|
female
|
white
|
el
|
20-29
| 27.3
| 1,920
| 1,080
| 58.14
| 24
|
51,483
|
female
|
white
|
el
|
20-29
| 24.4
| 1,920
| 1,080
| 54.39
| 24
|
51,484
|
female
|
white
|
el
|
20-29
| 13
| 1,920
| 1,080
| 32.24
| 25
|
51,485
|
female
|
white
|
el
|
20-29
| 13.4
| 1,920
| 1,080
| 37.16
| 25
|
51,486
|
female
|
white
|
el
|
20-29
| 15.4
| 1,920
| 1,080
| 30.88
| 25
|
51,487
|
female
|
white
|
el
|
20-29
| 27.6
| 1,920
| 1,080
| 64.72
| 25
|
51,488
|
female
|
white
|
el
|
20-29
| 21.1
| 1,920
| 1,080
| 46.16
| 25
|
51,489
|
female
|
white
|
el
|
20-29
| 26.2
| 1,920
| 1,080
| 54.76
| 25
|
51,490
|
female
|
white
|
el
|
20-29
| 34.7
| 1,920
| 1,080
| 77.8
| 25
|
51,491
|
female
|
white
|
el
|
20-29
| 41
| 1,920
| 1,080
| 93.28
| 25
|
About
We provide a comprehensive talking-head video dataset with over 50,000 videos, totaling more than 500+ hours of footage and featuring 20,841 unique identities from around the world.
Distribution
Detailing the format, size, and structure of the dataset:
-Total Size: 2.7TB
-Total Videos: 47,547
-Identities Covered: 20,841
-Resolution: 60% 4k(1980), 33% fullHD(1080)
-Formats: MP4
-Full-length videos with visible mouth movements in every frame.
-Minimum face size of 400 pixels.
-Video durations range from 20 seconds to 5 minutes.
-Faces have not been cut out, full screen videos including backgrounds.
Usage
This dataset is ideal for a variety of applications:
Face Recognition & Verification: Training and benchmarking facial recognition models.
Action Recognition: Identifying human activities and behaviors.
Re-Identification (Re-ID): Tracking identities across different videos and environments.
Deepfake Detection: Developing methods to detect manipulated videos.
Generative AI: Training high-resolution video generation models.
Lip Syncing Applications: Enhancing AI-driven lip-syncing models for dubbing and virtual avatars.
Background AI Applications: Developing AI models for automated background replacement, segmentation, and enhancement.
Coverage
Explaining the scope and coverage of the dataset:
Geographic Coverage: Worldwide
Time Range: Time range and size of the videos have been noted in the CSV file.
Demographics: Includes information about age, gender, ethnicity, format, resolution, and file size.
Languages Covered (Videos):
English: 23,038 videos
Portuguese: 1,346 videos
Spanish: 677 videos
Norwegian: 1,266 videos
Swedish: 1,056 videos
Korean: 848 videos
Polish: 1,807 videos
Indonesian: 1,163 videos
French: 1,102 videos
German: 1,276 videos
Japanese: 1,433 videos
Dutch: 1,666 videos
Indian: 1,163 videos
Czech: 590 videos
Chinese: 685 videos
Italian: 975 videos
Philipeans: 920 videos
Bulgaria: 340 videos
Philipeans: 920 videos
Bulgaria: 340 videos
Romanian: 1144 videos
Arabic: 1691 videos
Who Can Use It
List examples of intended users and their use cases:
Data Scientists: Training machine learning models for video-based AI applications.
Researchers: Studying human behavior, facial analysis, or video AI advancements.
Businesses: Developing facial recognition systems, video analytics, or AI-driven media applications.
Additional Notes
Ensure ethical usage and compliance with privacy regulations. The dataset’s quality and scale make it valuable for high-performance AI training. Potential preprocessing (cropping, down sampling) may be needed for different use cases. Dataset has not been completed yet and expands daily, please contact for most up to date CSV file. The dataset has been divided into 100GB zipped files and is hosted on a private server (with the option to upload to the cloud if needed). To verify the dataset's quality, please contact me for the full CSV file. I’d be happy to provide example videos selected by the potential buyer.
https://lipsynthesis.com/dataset
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