Zero-Shot Action Recognition

16 papers with code • 5 benchmarks • 4 datasets

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Most implemented papers

Learning a Deep Embedding Model for Zero-Shot Learning

lzrobots/DeepEmbeddingModel_ZSL CVPR 2017

In this paper we argue that the key to make deep ZSL models succeed is to choose the right embedding space.

Evaluation of Output Embeddings for Fine-Grained Image Classification

mvp18/Popular-ZSL-Algorithms CVPR 2015

Image classification has advanced significantly in recent years with the availability of large-scale image sets.

Label-Embedding for Image Classification

mvp18/Popular-ZSL-Algorithms 30 Mar 2015

Attributes act as intermediate representations that enable parameter sharing between classes, a must when training data is scarce.

Cross-Modal and Hierarchical Modeling of Video and Text

Sha-Lab/CMHSE ECCV 2018

Similarly, a paragraph may contain sentences with different topics, which collectively conveys a coherent message or story.

Out-of-Distribution Detection for Generalized Zero-Shot Action Recognition

naraysa/gzsl-od CVPR 2019

We introduce an out-of-distribution detector that determines whether the video features belong to a seen or unseen action category.

I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs

junyuGao/Zero-Shot-Action-Recognition-with-Two-Stream-GCN Proceedings of the AAAI Conference on Artificial Intelligence 2019

To effectively leverage the knowledge graph, we design a novel Two-Stream Graph Convolutional Network (TS-GCN) consisting of a classifier branch and an instance branch.

Learning Spatiotemporal Features via Video and Text Pair Discrimination

MCG-NJU/CPD-Video 16 Jan 2020

In addition, our CPD model yields a new state of the art for zero-shot action recognition on UCF101 by directly utilizing the learnt visual-textual embeddings.

Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications

bbrattoli/ZeroShotVideoClassification CVPR 2020

Our training procedure builds on insights from recent video classification literature and uses a trainable 3D CNN to learn the visual features.

Elaborative Rehearsal for Zero-shot Action Recognition

DeLightCMU/ElaborativeRehearsal ICCV 2021

However, due to the complexity and diversity of actions, it remains challenging to semantically represent action classes and transfer knowledge from seen data.