The goal of the Kinetics dataset is to help the computer vision and machine learning communities advance models for video understanding. Given this large human action classification dataset, it may be possible to learn powerful video representations that transfer to different video tasks.
The Kinetics-700-2020 dataset will be used for this challenge. Kinetics-700-2020 is a large-scale, high-quality dataset of YouTube video URLs which include a diverse range of human focused actions. The aim of the Kinetics dataset is to help the machine learning community create more advanced models for video understanding. It is an approximate super-set of both Kinetics-400, released in 2017, Kinetics-600, released in 2018 and Kinetics-700, released in 2019.
The dataset consists of approximately 650,000 video clips, and covers 700 human action classes with at least 700 video clips for each action class. Each clip lasts around 10 seconds and is labeled with a single class. All of the clips have been through multiple rounds of human annotation, and each is taken from a unique YouTube video. The actions cover a broad range of classes including human-object interactions such as playing instruments, as well as human-human interactions such as shaking hands and hugging.
More information about how to download the Kinetics dataset is available here.
Because of these letdowns, she refers to herself as (Miss Unlucky) and tells her ex he is "foutu" because he has lost her trust and ruined the relationship. The Andrey Vertuga Remix
A faster, more upbeat version released for the 2012 anniversary 3. Key Audio Characteristics Vocal Preservation: ingrid tu es foutu andrey vertuga remix 4 best
If you are searching for on YouTube or Reddit, here is a second-by-second listening guide to confirm you have the correct file. Because of these letdowns, she refers to herself
The mysterious "Ingrid, Tu Es Foutu (Andrei Vertuga Remix 4 Best)" likely represents an experimental reimagining of the original track. Described as a "remix 4 best," the version could incorporate Vertuga’s signature brooding, almost Gothic undertones, layering his Russian-inflected vocals or guitar textures over the frenetic French punk structure. The result might be a clashing yet harmonious blend of languages (French and Russian), with samples of Vertuga’s haunting melodies merging with Les Salopiauds’ abrasive, politically charged riffs. The "4 best" moniker (possibly a typo for "4 Beste" or a tribute to Beste Band der Welt , a punk label) suggests a version created for fans, perhaps as a limited-release homage to punk’s DIY ethos. The mysterious "Ingrid, Tu Es Foutu (Andrei Vertuga
Vertuga is a master of tension. He strips away the bass, raises the pitch of the risers, and isolates the vocal melody. This creates a moment of sing-along nostalgia before releasing the energy of the drop.
Years later, Russian producer Andrey Vertuga reimagined this tale for a new generation of club-goers.
1. Possible to use ImageNet checkpoints?
We allow finetuning from public ImageNet checkpoints for the supervised track -- but a link to the specific checkpoint should be provided with each submission.
2. Possible to use optical flow?
Flow can be used as long as not trained on external datasets, except if they are synthetic.
3. Can we train on test data without labels (e.g. transductive)?
No.
4. Can we use semantic class label information?
Yes, for the supervised track.
5. Will there be special tracks for methods using fewer FLOPs / small models or just RGB vs RGB+Audio in the self-supervised track?
We will ask participants to provide the total number of model parameters and the modalities used and plan to create special mentions for those doing well in each setting, but not specific tracks.