HyperAIHyperAI

Command Palette

Search for a command to run...

3 months ago

Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022

Li Gu Zhixiang Chi Huan Liu Yuanhao Yu Yang Wang

Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022

Abstract

In this work, we present the winning solution for ORBIT Few-Shot Video Object Recognition Challenge 2022. Built upon the ProtoNet baseline, the performance of our method is improved with three effective techniques. These techniques include the embedding adaptation, the uniform video clip sampler and the invalid frame detection. In addition, we re-factor and re-implement the official codebase to encourage modularity, compatibility and improved performance. Our implementation accelerates the data loading in both training and testing.

Benchmarks

BenchmarkMethodologyMetrics
few-shot-image-classification-on-orbitProtoNetsVideo
Frame accuracy: 71.69

Build AI with AI

From idea to launch — accelerate your AI development with free AI co-coding, out-of-the-box environment and best price of GPUs.

AI Co-coding
Ready-to-use GPUs
Best Pricing
Get Started

Hyper Newsletters

Subscribe to our latest updates
We will deliver the latest updates of the week to your inbox at nine o'clock every Monday morning
Powered by MailChimp
Improving ProtoNet for Few-Shot Video Object Recognition: Winner of ORBIT Challenge 2022 | Papers | HyperAI