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The 20BN-jester Dataset V1


Introduction

The 20BN-JESTER dataset is a large collection of densely-labeled video clips that show humans performing pre-definded hand gestures in front of a laptop camera or webcam. The dataset was created by a large number of crowd workers. It allows for training robust machine learning models to recognize human hand gestures. It is available free of charge for academic research. Commercial licenses are available upon request.

A paper with supplementary material can be found here.

Sliding Two Fingers Down
Swiping Left
Thumb Up

Data format

The video data is provided as one large TGZ archive, split into parts of 1 GB max. The total download size is 22.8 GB. The archive contains directories numbered from 1 to 148092. Each directory corresponds to one video and contains JPG images with height 100px and variable width. The JPG images were extracted from the orginal videos at 12 frames per seconds. The filenames of the JPGs start at 00001.jpg. The number of JPGs varies as the length of the original videos varies.

Terms of use

This dataset be used for academic research free of charge under the below license agreement. If you seek to use the data for commercial purposes please contact us.

Download Dataset

Please register or log in to download the dataset.


20BN-JESTER-DATASET
Total number of videos
148,092
Training Set
118,562
Validation Set
14,787
Test Set (w/o labels)
14,743
Labels
27
12,416
Doing other things
5,444
Drumming Fingers
5,344
No gesture
5,379
Pulling Hand In
5,315
Pulling Two Fingers In
5,434
Pushing Hand Away
5,358
Pushing Two Fingers Away
5,031
Rolling Hand Backward
5,165
Rolling Hand Forward
5,314
Shaking Hand
5,410
Sliding Two Fingers Down
5,345
Sliding Two Fingers Left
5,244
Sliding Two Fingers Right
5,262
Sliding Two Fingers Up
5,413
Stop Sign
5,303
Swiping Down
5,160
Swiping Left
5,066
Swiping Right
5,240
Swiping Up
5,460
Thumb Down
5,457
Thumb Up
3,980
Turning Hand Clockwise
4,181
Turning Hand Counterclockwise
5,307
Zooming In With Full Hand
5,355
Zooming In With Two Fingers
5,330
Zooming Out With Full Hand
5,379
Zooming Out With Two Fingers

Leaderboard

If you have been successful in creating a classification model based on the training set and it performs well on the validation set, we encourage you to run your model on the test set (which is published without any class labels, as you might have noticed). Please prepare a .csv file with the video's id in the first column and your predicted class label (as a string matching the wording used in the training and validation sets). As a separator, please use a semicolon. You can then upload your .csv file here (user login required) to be ranked in the leaderboard and to benchmark your approach against that of other machine learners. We are looking forward to your submission.

Rank
Name
Approach
Score
1
BOE_IOT_AIBD
4 months ago

Fusion_TSN_LSTM

97.09%
2
Anonymous
29 days ago

CVPR2020Submission

97.09%
3
Huawei Noah's Ark Toronto Laboratory Team
6 months ago

RFEEN, 20 Crops

97.06%
4
Anonymous
3 months ago

rgb 12F

96.95%
5
Anonymous
3 months ago

rgb 8F

96.82%
6
Gaurav Kumar Singh
about 1 year ago

Ford's Gesture Recognition System

96.77%
7
Anonim
about 1 year ago

96.74%
8
Anonymous
almost 2 years ago

DRX3D

96.6%
9
Anonymous
about 1 year ago

96.56%
10
Okan Köpüklü
almost 2 years ago

Motion Fused Frames (MFFs)
Code: https://github.com/okankop/MFF-pytorch
Article: https://arxiv.org/pdf/1804.07187.pdf
Contact:okankopuklu@gmail.com

96.28%
11
Mohamad ALjazaery @Midea
over 1 year ago

Spatiotemporal Two Streams network

96.28%
12
Anonymous
over 1 year ago

3D CNN Architecture

96.24%
13
Anonymous
almost 2 years ago

Motion Feature Network (MFNet)

96.22%
14
Anonymous
about 1 year ago

RNP

95.96%
15
Jingyao Wang
about 1 year ago

95.96%
16
jiaming huang
26 days ago

95.94%
17
Anonymous
8 months ago

ResNext 101

95.87%
18
anonymous
about 1 year ago

SSNet RGB resnet

95.79%
19
Anonymous
9 days ago

95.79%
20
Anonymous
about 1 year ago

TVB

95.71%
21
Ke Yang (NUDT_PDL)
almost 2 years ago

Temporal Pyramid Relation Network for Video-Based Gesture Recognition,2018 25th IEEE International Conference on Image Processing (ICIP)

95.34%
22
Anonymous
almost 2 years ago

DIN

95.31%
23
Anonymous
9 months ago

95.14%
24
Guangming Zhu
almost 2 years ago

95.01%
25
Test
6 months ago

TRN - 8 segments

94.95%
26
SJ
almost 2 years ago

94.87%
27
Roy Amante Salvador
8 months ago

3D CNN - Multi time scale evaluation

94.85%
28
Anonymous
10 months ago

8frames rgb

94.81%
29
Anonymous
about 2 years ago

TRN (CVPR'18 submission)

94.78%
30
Thomas Friedel
over 1 year ago

94.74%
31
ALAB
about 1 year ago

TRN + BNInception

94.5%
32
Anonymous
8 months ago

Anonymous

94.49%
33
Anonymous
10 months ago

final test
label+string

94.47%
34
Shuai
11 months ago

slowfast res50

94.46%
35
Roy Salvador
8 months ago

3D CNN for transfer learning

94.26%
36
Eren Gölge
about 2 years ago

Besnet

94.23%
37
Wu Jie @ DLUT-SIE
8 months ago

3D_GesNet

93.99%
38
Wu Jie @ DLUT-SIE
8 months ago

3D-GesNet(only rgb)

93.99%
39
Guillaume Berger
about 2 years ago

93.87%
40
XM
about 1 year ago

ECO

93.82%
41
ming chen
12 days ago

2D and 3D fused network

93.8%
42
Anonymous
9 months ago

TRN-E

93.58%
43
Zubair
about 2 months ago

Inceptionv2 - TRN16

93.55%
44
Francesco Dalla Serra
over 1 year ago

One Stream Modified-I3D

93.41%
45
Baptist
almost 2 years ago

93.11%
46
Fábio Baldissera
6 months ago

RT C3D - 16 Frames
Code: https://github.com/fabiopk

92.65%
47
RyMult
4 months ago

91.61%
48
rml
4 months ago

91.61%
49
Prasad Pai
12 months ago

91.45%
50
wuxia tu
about 1 month ago

prune_net

91.22%
51
Oskar Holmberg, Filip Granqvist
over 1 year ago

90.52%
52
anonymous
over 1 year ago

Modified C3D

89.26%
53
qi yuan
11 months ago

87.94%
54
Haibing Huang
about 1 year ago

CNN+LSTM

86.31%
55
Arnaud Steinmetz
about 1 year ago

3D ResNet 101

85.99%
56
John Emmons
about 2 years ago

VideoLSTM

85.86%
57
Olivier Valery
about 1 year ago

3D convolutional neural network

85.49%
58
qiu feng
about 1 month ago

Result_63

85.31%
59
Damien MENIGAUX
about 2 years ago

ConvLSTM

82.76%
60
Joanna Materzyńska
over 2 years ago

Twenty Billion Neuron's Jester System

82.34%
61
lbjbx
7 months ago

3d+resnet18

81.55%
62
Wei-Cheng Lin
3 months ago

77.89%
63
Liam Schoneveld
5 months ago

Basic finetune MobileNetV2 (pretrained imagenet) + LSTM output

74.4%
64
GY@CAD
4 months ago

interframe-difference LSTM

73.22%
65
yuzhe zhou
4 months ago

Mobilenetv3-LSTM

71.72%
66
ke yang(BUPT)
over 1 year ago

3D ResNet

68.13%
67
Victor
over 1 year ago

3D-ResNet101 trained on Kinetics

59.01%
68
CS2R_Muneer
23 days ago

57.04%
69
FeiHu Jiang
2 months ago

2D+3D

44.04%
70
Yu Zhu
over 2 years ago

10.52%
71
Ming
over 1 year ago

Test

4.0%
72
Anonymous
10 months ago

3.97%
73
Konfuzius
over 2 years ago

Just random guessing...

3.65%
74
Anonymous
10 months ago

rgb_only
test label (from 0 to 26)

0.0%
75
Anonymous
8 months ago

ResNext 101

0.0%
76
Fabio B.
6 months ago

[test_run] 3D RGB 16F

0.0%
77
ozgur
5 months ago

0.0%



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