# "Knights": First Place Submission for VIPriors21 Action Recognition Challenge at ICCV 2021

Source: ["Knights": First Place Submission for VIPriors21 Action Recognition Challenge at ICCV 2021](<https://www.sota2.com/research/paper/68fa6b111e209131cea2be75>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:39:16.015Z

Authors: Ishan Dave, Naman Biyani, Brandon Clark, Rohit Gupta, Yogesh Rawat, Mubarak Shah

Published: 2021-10-14T22:47:31.000Z

## Abstract

This technical report presents our approach "Knights" to solve the action recognition task on a small subset of Kinetics-400 i.e. Kinetics400ViPriors without using any extra-data. Our approach has 3 main components: state-of-the-art Temporal Contrastive self-supervised pretraining, video transformer models, and optical flow modality. Along with the use of standard test-time augmentation, our proposed solution achieves 73% on Kinetics400ViPriors test set, which is the best among all of the other entries Visual Inductive Priors for Data-Efficient Computer Vision's Action Recognition Challenge, ICCV 2021.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2110.07758>)

[PDF](<https://arxiv.org/pdf/2110.07758.pdf>)