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.
The impact of "So Much Pain" (Izzamuzzic Remix) lies in its ability to evoke empathy and understanding. The song humanizes 2Pac, showcasing his vulnerability and emotional depth. It also serves as a reminder of the ongoing struggles faced by marginalized communities, sparking conversations about social justice and reform.
The song’s relevance persists in contemporary discourse, reflecting ongoing struggles against systemic racism and urban violence. Its remix format—a hallmark of hip-hop’s DIY ethos—also underscores the genre’s capacity for reinterpretation, allowing 2Pac’s message to evolve with successive generations. 2pac - so much pain -izzamuzzic remix- lyrics
When an iconic track gets a modern remix, it’s more than just a beat swap—it’s a conversation across generations. That’s exactly what happens with , reborn by the talented producer Izzamuzzic . In this post we’ll explore the original’s background, dissect the sonic choices Izzamuzzic made, and reflect on why the remix feels both nostalgic and forward‑looking. The impact of "So Much Pain" (Izzamuzzic Remix)
"So Much Pain (Izzamuzzic Remix)" acts as a bridge between generations. It takes the profound lyrical sorrow of one of hip-hop’s greatest poets and repurposes it for the high-adrenaline, bass-heavy environment of modern Phonk music. While it sacrifices That’s exactly what happens with , reborn by
Lord, tell me why we suffer so much pain?
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.