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Action Classification

42 papers with code ·

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Deep Concept-wise Temporal Convolutional Networks for Action Localization

26 Aug 2019PaddlePaddle/models

In this paper, we empirically find that stacking more conventional temporal convolution layers actually deteriorates action classification performance, possibly ascribing to that all channels of 1D feature map, which generally are highly abstract and can be regarded as latent concepts, are excessively recombined in temporal convolution.

ACTION CLASSIFICATION ACTION CLASSIFICATION ACTION LOCALIZATION

Audiovisual SlowFast Networks for Video Recognition

23 Jan 2020facebookresearch/SlowFast

We present Audiovisual SlowFast Networks, an architecture for integrated audiovisual perception.

ACTION CLASSIFICATION ACTION CLASSIFICATION VIDEO RECOGNITION

Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

CVPR 2017 deepmind/kinetics-i3d

The paucity of videos in current action classification datasets (UCF-101 and HMDB-51) has made it difficult to identify good video architectures, as most methods obtain similar performance on existing small-scale benchmarks.

ACTION CLASSIFICATION ACTION RECOGNITION SKELETON BASED ACTION RECOGNITION

ECO: Efficient Convolutional Network for Online Video Understanding

ECCV 2018 mzolfaghari/ECO-efficient-video-understanding

In this paper, we introduce a network architecture that takes long-term content into account and enables fast per-video processing at the same time.

Ranked #21 on Action Recognition on Something-Something V1 (using extra training data)

ACTION CLASSIFICATION ACTION CLASSIFICATION ACTION RECOGNITION VIDEO CAPTIONING VIDEO RETRIEVAL VIDEO UNDERSTANDING

Graph Convolutional Networks for Temporal Action Localization

ICCV 2019 Alvin-Zeng/PGCN

Then we apply the GCNs over the graph to model the relations among different proposals and learn powerful representations for the action classification and localization.

ACTION CLASSIFICATION ACTION CLASSIFICATION TEMPORAL ACTION LOCALIZATION

Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs

CVPR 2016 zhengshou/scnn

To address this challenging issue, we exploit the effectiveness of deep networks in temporal action localization via three segment-based 3D ConvNets: (1) a proposal network identifies candidate segments in a long video that may contain actions; (2) a classification network learns one-vs-all action classification model to serve as initialization for the localization network; and (3) a localization network fine-tunes on the learned classification network to localize each action instance.

ACTION CLASSIFICATION ACTION CLASSIFICATION TEMPORAL ACTION LOCALIZATION TEMPORAL LOCALIZATION