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 2007 crime thriller Shootout at Lokhandwala remains a defining film in Indian cinema’s gangster genre. Directed by Apoorva Lakhia, this film chronicled the real-life 1991 Lokhandwala Complex shootout, a pivotal moment in Mumbai's criminal history. For many, finding the quality version of Shootout at Lokhandwala on platforms like Filmywap is crucial for experiencing the high-stakes, action-packed narrative that brought the infamous Maya Dolas to the big screen. What Made Shootout at Lokhandwala So Special?
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The film meticulously recreated the claustrophobic, high-stakes environment of the Lokhandwala Complex during the real four-hour gunfight, keeping audiences on the edge of their seats.
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(based on the real A.A. Khan), a "hardcase" officer determined to clean the streets. The Moral Arbiter:
, directed by Apoorva Lakhia, is a landmark crime thriller based on the real-life 1991 Lokhandwala Complex shootout
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Vivek Oberoi’s portrayal of Maya Dolas is often cited as one of the most underrated performances of the decade. His transformation from a volatile henchman to a feared don was chilling, providing a perfect foil to Sanjay Dutt’s authoritative police officer. The chemistry among the gang members—often terrifying, sometimes darkly humorous—gave the film a texture that standard action movies lacked.
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.