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.
In Bengaluru, a 22-year-old girl tells her mother, "I am not going to stand in the kitchen for three hours to make dosa for a joint family. I am buying a dosa maker machine." The mother is horrified. "What will the neighbors say? That you are lazy?" The daughter replies, "No. That I am smart." After a three-day silent treatment, the mother caves. They buy the machine. The neighbors come over to "see" the machine. They all go home and order the same machine on Amazon. Progress is slow, but it is happening.
Many families still operate under a hierarchical structure where three to four generations live together. These households often share a common kitchen and "purse," with the eldest male (patriarch) or his wife managing daily operations.
Daily life often involves meticulous planning—from ensuring the "milkman" has delivered to the secondary ritual of "Diwali-level" deep cleaning that seems to start months in advance. The Shared Table:
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In Indian culture, respect for elders is deeply ingrained. Children are taught from a young age to show deference to their seniors, using honorific titles, and seeking their blessings. Elders, in turn, share their wisdom, experience, and guidance, helping to shape the values and personalities of the younger generation.
The day begins early, often before the sun rises. In many homes, the first sound is the sweeping of the front porch, followed by the drawing of a rangoli (geometric chalk patterns) to welcome prosperity.
Indian family life is a beautiful paradox—it is chaotic yet organized, traditional yet evolving. It’s a lifestyle built on the idea that "we" is always more important than "I." From the shared meals to the collective celebrations of even the smallest milestones, the Indian daily story is a testament to the enduring power of human connection. In Bengaluru, a 22-year-old girl tells her mother,
Around 5:30 PM, the second round of chai is brewed. This is the moment when children return from coaching classes and adults walk through the door. The evening tea is accompanied by light snacks like rusk (biscuits), samosas , or namkeen (savory mixtures). It serves as a decompression chamber, allowing family members to vent about their day and transition from their public personas back into their domestic roles. The Street Culture
| ✅ Action | ❌ What to Avoid | |----------|-----------------| | Verify the source before resharing. | Forward the clip blindly because it’s “trending.” | | Consider the potential harm to the people involved. | Post or comment with hateful language or accusations. | | Use platform tools to report non‑consensual intimate content. | Encourage “best cheat” memes that mock the victim. | | If you’re a journalist, seek comment from the subject or their legal representative. | Publish the video without context or verification. | | Remember that “viral” does not equal “newsworthy.” | Assume the clip is an accurate representation of reality. |
Even if components of lunch are repurposed, fresh rotis (flatbreads) are puffed on the open flame right as people sit down to eat. The matriarch of the house often stands by the stove, serving hot bread directly to plates, eating only after the rest of the family has been well-fed. The Digital Paradox That you are lazy
By mid-morning, the house empties as adults head to work and children go to school. In residential neighborhoods, the streets come alive with local vendors. Door-to-door salesmen call out, selling fresh vegetables, knife-sharpening services, or collecting recyclable newspapers. For those remaining at home, this time is dedicated to meticulous house cleaning and preparing the heavy afternoon lunch. The Evening Reunion
Saturdays are often reserved for weekly grocery runs to the local sabzi mandi (vegetable market) or the supermarket, combined with wardrobe shopping for upcoming festivals or weddings.
The Indian family lifestyle is a chaotic, noisy, loving, frustrating, and utterly addictive masterpiece. It is a place where boundaries are blurred, where the individual often disappears into the collective, but where no one ever has to be truly alone.
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.