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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?

 Ranked #1 on Egocentric Activity Recognition on EPIC-KITCHENS-55 (Actions Top-1 (S2) metric)

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

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

Convolutional Spiking Neural Networks for Spatio-Temporal Feature Extraction

27 Mar 2020aa-samad/conv_snn

Spiking neural networks (SNNs) can be used in low-power and embedded systems (such as emerging neuromorphic chips) due to their event-based nature.

ACTIVITY RECOGNITION IN VIDEOS EVENT DATA CLASSIFICATION IMAGE CLASSIFICATION VIDEO CLASSIFICATION