Library to recognise and classify faces. face-recognitionface-detectionfew-shot-recognitionfew-shot-classifcation UpdatedJul 26, 2021 Python Code for "Improved Few-Shot Visual Classification" meta-learningfew-shot-learningfew-shot-recognitionfew-shot-classifcation ...
2.3TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition (BMVC2019) 这篇文章主要是受到text sequence matching任务的启发,将few-shot recognition任务也当成匹配任务进行处理,将一个视频看成是segment-level的序列数据。 文章方法主要包含两个部分: embedding module; relation modul...
Few-shot action recognition aims to recognize actions in test videos based on limited annotated data of target action classes. The dominant approaches project videos into a metric space and classify videos via nearest neighboring. They mainly measure video similarities using global or temporal alignment...
Few-shot action recognition aims to recognize novel action classes with limited labeled samples and has recently received increasing attention. The core objective of few-shot action recognition is to enhance the discriminability of feature representations. In this paper, we propose a novel multi-view ...
Fuxin Li, Mei Chen ICCV 2021|October 2021 We present MetaUVFS as the first Unsupervised Meta-learning algorithm for Video Few-Shot action recognition. MetaUVFS leverages over 550K unlabeled videos to train a two-stream 2D and 3D CNN architecture via contrastive learn...
1. Compound Memory Networks (ECCV2018)：提出了一种复合记忆网络，通过meta-learning处理视频动作识别。网络结构分为multi-saliency embedding和key-value memory，用于表示视频特征和对应动作标签，支持快速检索和动态更新。2. Embodied One-Shot Video Recognition (ACM Multimedia 2019)：实验室的研究利用...
Few-shot Action Recognition with Prototype-centered Attentive Learning阅读笔记,程序员大本营,技术文章内容聚合第一站。
python3 wacv2020 cvpr2020 fewshot-learning Updated Jan 17, 2022 Python steb6 / ISBFSAR Star 14 Code Issues Pull requests Interactive Skeleton Based Few Shot Action Recognition python pytorch human-pose-estimation human-activity-recognition pose-estimation open-set gaze-estimation few-shot few...
Temporal-Relational CrossTransformers for Few-Shot Action Recognition Toby Perrett Alessandro Masullo Tilo Burghardt Majid Mirmehdi Dima Damen .@bristol.ac.uk Department of Computer Science, University of Bristol, UK Abstract We propose a novel approach to few-shot a...
We present a generative framework for zero-shot action recognition where some of the possible action classes do not occur in the training data. Our approach is based on modeling each action class using a probability distribution whose parameters are functions of the attribute vector representing that...