EPIC-KITCHENS-55 baselines for Action Recognition
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Updated
Jul 14, 2020 - Python
EPIC-KITCHENS-55 baselines for Action Recognition
☕ EPIC-KITCHENS-55 dataset python library
🌱 Starter kit for working with the EPIC-KITCHENS-55 dataset for action recognition or anticipation
Epic Kitchens Object Detector and Feature Extractor using Faster-RCNN with Detectron2
Simple PyTorch Dataset for the EPIC-Kitchens-55 and EPIC-Kitchens-100 that handles frames and features (rgb, optical flow, and objects) for the Action Recognition and the Action Anticipation Tasks!
Various flavours of algorithms attempted to solve the EPIC Kitchens Challenge
Lightning implementation of TA3N, the SOTA model for Unsupervised Action Domain Adaptation.
Attention-based Temporal Binding Network
Attribution (or visual explanation) methods for understanding video classification networks. Demo codes for WACV2021 paper: Towards Visually Explaining Video Understanding Networks with Perturbation.
Multimodal version of SlowFast (Vision + Audio inputs)
Invariant Risk Minimization on EPIC KITCHEN ResNet 50 Features
This repo provides some filters for NeRF data preparation for the EPIC Kitchens Dataset. We will be releasing the dataset soon.
A video feature extractor using the epic fusion model
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