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 film explores the "true pain" of a cricketer as Jeeva faces numerous hurdles, from his father's initial disapproval to the deep-seated communal and caste-based politics within the selection committees of the Tamil Nadu Cricket Association.
The story follows (played by Vishnu Vishal), a talented lower-middle-class youth whose life revolves around his passion for cricket and his idol, Sachin Tendulkar. jeeva tamil movie
The movie concludes with Jeeva emerging victorious, having made amends with his past and found a new sense of purpose. He and Sriya confess their love for each other, and the movie ends on a hopeful note. The film explores the "true pain" of a
The opening portion of the film is a nostalgic trip for anyone who grew up playing "gully cricket" (street cricket). It captures the nuances—the fights over LBW decisions, the struggle to find a decent ground in a congested city, and the camaraderie among friends. This section establishes Jeeva’s natural talent, specifically his prowess as a spin bowler. It is lighthearted, romantic (introducing the love interest, Jenny, played by Sri Divya), and focuses on the pure joy of the sport. He and Sriya confess their love for each
The film is available on (official upload by producers) and sometimes on Sun NXT . DVD copies are rare.
Jeeva Genre: Action, Thriller Plot:
The film features a strong ensemble that brings authenticity to the sports-centric narrative:
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.