Video-understanding-dataset
Please feel free to pull a request.
Note: ActivityNet v1.3, Kinetics-600, Moments in time, AVA will be used at ActivityNet challenge 2018
| Dataset |
Paper |
Website |
Category |
#Examples |
#Classes |
Duration |
Organizer |
SOTA performance |
| UCF101 |
PDF |
Link |
human action |
13,320 |
101 |
<10s |
UCF |
98% (DeepMind I3D) |
| HMDB51 |
PDF |
Link |
human action |
6,766 |
51 |
<10s |
Brown |
80.7% (DeepMind I3D) |
| ActivityNet v1.3 |
PDF |
Link |
human activities |
~20,000 |
200 |
- |
ActivityNet |
8.83% err (iBUG) |
| Charades |
PDF |
Link |
daily human activities |
9,848 |
157 |
- |
AI2 |
0.3441 mAP (DeepMind I3D) |
| Kinetics |
PDF |
Link |
human action |
~500,000 |
600 |
10s |
DeepMind |
- |
| Sports-1M |
PDF |
Link |
sports |
~1 million |
478 |
5m36s |
Google & Stanford |
- |
| YouTube-8M |
PDF |
Link |
visual contents |
~7 million |
4716 |
120-500s |
Google Cloud |
85% GAP (WILLOW) |
| FCVID |
PDF |
Link |
visual contents |
91,223 |
239 |
100s+ |
Fudan-Columbia |
- |
| Something-Something |
PDF |
Link |
action with objects |
108,499 |
174 |
~4s |
TwentyBN |
- |
| Moments in Time |
PDF |
Link |
action or activity |
~1 million |
339 |
3s |
MIT-IBM Watson |
- |
| SLAC |
arXiv |
Link |
recognition and localization |
520K |
200 |
~30.6s |
MIT and Facebook |
- |
Temporal Action Detection
| Dataset |
Paper |
Website |
#Examples |
Organizer |
SOTA performance |
| THUMOS2014 |
PDF |
Link |
9.682 |
UCF |
- |
| ActivityNet(v1.3) |
PDF |
Link |
~20,000 |
ActivityNet |
0.344(SJTU & Columbia ) |
| Broad Video Highlights |
- |
Link |
18000 |
Baidu |
- |
Spatio-temporally Localized Atomic Visual Actions
| Dataset |
Paper |
Website |
#Examples |
#Classes |
Organizer |
SOTA performance |
| AVA |
arXiv |
Link |
57.6k |
80 |
Google & Berkeley |
- |
| Dataset |
Paper |
Website |
#Examples |
#Classes |
Organizer |
SOTA performance |
| Jester |
- |
Link |
148,092 |
27 |
TwentyBN |
95.34%(Ke Yang, NUDT_PDL) |
| Dataset |
Paper |
Website |
Context |
#Examples |
Organizer |
SOTA performance |
| MPII-MD |
PDF |
Link |
movie |
68,337 clips with 68,375 sentences |
MPII |
- |
| MSR-VTT |
PDF |
Link |
20 categories |
10,000 clips wth 200,000 sentences |
MSR |
- |
| Charades |
PDF |
Link |
human activity |
9,848 clips wth 27,847 sentences |
AI2 |
- |
| Densevid |
PDF |
Link |
event |
20k clips and 100k sentences |
Stanford, ActivityNet |
- |
| Dataset |
Paper |
Website |
Task |
#Examples |
Organizer |
SOTA performance |
| MovieQA |
PDF |
Link |
question-answering in movies |
408 movies & 14944 QAs |
UToronto |
- |
| MarioQA |
PDF |
Link |
reasoning events in game videos |
187,757 examples with 92,874 QAs |
POSTECH |
- |