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Activity Recognition

59 papers with code · Computer Vision

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Greatest papers with code

Large-scale weakly-supervised pre-training for video action recognition

CVPR 2019 microsoft/computervision-recipes

Second, frame-based models perform quite well on action recognition; is pre-training for good image features sufficient or is pre-training for spatio-temporal features valuable for optimal transfer learning?

#2 best model for Action Classification on Kinetics-400 (using extra training data)

ACTION CLASSIFICATION ACTION RECOGNITION IN VIDEOS ACTIVITY RECOGNITION IN VIDEOS TRANSFER LEARNING

Temporal Relational Reasoning in Videos

ECCV 2018 metalbubble/TRN-pytorch

Temporal relational reasoning, the ability to link meaningful transformations of objects or entities over time, is a fundamental property of intelligent species.

ACTION CLASSIFICATION ACTION RECOGNITION IN VIDEOS COMMON SENSE REASONING HUMAN-OBJECT INTERACTION DETECTION RELATIONAL REASONING

TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity Recognition

30 Mar 2017jeffreyhuang1/two-stream-action-recognition

We demonstrate that using both RNNs (using LSTMs) and Temporal-ConvNets on spatiotemporal feature matrices are able to exploit spatiotemporal dynamics to improve the overall performance.

ACTION CLASSIFICATION ACTION RECOGNITION IN VIDEOS VIDEO UNDERSTANDING

Multivariate LSTM-FCNs for Time Series Classification

14 Jan 2018titu1994/LSTM-FCN

Over the past decade, multivariate time series classification has received great attention.

ACTIVITY RECOGNITION TEMPORAL ACTION LOCALIZATION TIME SERIES TIME SERIES CLASSIFICATION

Real-world Anomaly Detection in Surveillance Videos

CVPR 2018 WaqasSultani/AnomalyDetectionCVPR2018

To avoid annotating the anomalous segments or clips in training videos, which is very time consuming, we propose to learn anomaly through the deep multiple instance ranking framework by leveraging weakly labeled training videos, i. e. the training labels (anomalous or normal) are at video-level instead of clip-level.

ACTIVITY RECOGNITION ANOMALY DETECTION IN SURVEILLANCE VIDEOS MULTIPLE INSTANCE LEARNING

NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding

12 May 2019shahroudy/NTURGB-D

Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition.

ACTIVITY RECOGNITION ONE-SHOT 3D ACTION RECOGNITION TEMPORAL ACTION LOCALIZATION

Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors

22 Aug 2017guillaume-chevalier/HAR-stacked-residual-bidir-LSTMs

Human activity recognition (HAR) has become a popular topic in research because of its wide application.

HUMAN ACTIVITY RECOGNITION

Representation Flow for Action Recognition

CVPR 2019 piergiaj/representation-flow-cvpr19

Our representation flow layer is a fully-differentiable layer designed to capture the `flow' of any representation channel within a convolutional neural network for action recognition.

ACTION CLASSIFICATION ACTION RECOGNITION IN VIDEOS ACTIVITY RECOGNITION IN VIDEOS OPTICAL FLOW ESTIMATION VIDEO UNDERSTANDING

Object Level Visual Reasoning in Videos

ECCV 2018 fabienbaradel/object_level_visual_reasoning

Human activity recognition is typically addressed by detecting key concepts like global and local motion, features related to object classes present in the scene, as well as features related to the global context.

HUMAN ACTIVITY RECOGNITION OBJECT DETECTION VISUAL REASONING

Hierarchical Attentive Recurrent Tracking

NeurIPS 2017 akosiorek/hart

Class-agnostic object tracking is particularly difficult in cluttered environments as target specific discriminative models cannot be learned a priori.

ACTIVITY RECOGNITION OBJECT TRACKING