Video Understanding
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Greatest papers with code
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
CVPR 2018
• tensorflow/models
• 
The AVA dataset densely annotates 80 atomic visual actions in 430 15-minute video clips, where actions are localized in space and time, resulting in 1. 58M action labels with multiple labels per person occurring frequently.
ACTION LOCALIZATION VIDEO UNDERSTANDING ZERO-SHOT ACTION RECOGNITION
TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity Recognition
• chihyaoma/Activity-Recognition-with-CNN-and-RNN
• 
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 ACTIVITY RECOGNITION VIDEO CLASSIFICATION VIDEO UNDERSTANDING
Learnable pooling with Context Gating for video classification
• antoine77340/Youtube-8M-WILLOW
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In particular, we evaluate our method on the large-scale multi-modal Youtube-8M v2 dataset and outperform all other methods in the Youtube 8M Large-Scale Video Understanding challenge.
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.
End-to-End Learning of Motion Representation for Video Understanding
Despite the recent success of end-to-end learned representations, hand-crafted optical flow features are still widely used in video analysis tasks.
ACTION RECOGNITION IN VIDEOS OPTICAL FLOW ESTIMATION VIDEO UNDERSTANDING
TSM: Temporal Shift Module for Efficient Video Understanding
• MIT-HAN-LAB/temporal-shift-module
•
The explosive growth in video streaming gives rise to challenges on efficiently extracting the spatial-temporal information to perform video understanding at low computation cost.
The Monkeytyping Solution to the YouTube-8M Video Understanding Challenge
This article describes the final solution of team monkeytyping, who finished in second place in the YouTube-8M video understanding challenge.
Temporal Tessellation: A Unified Approach for Video Analysis
ICCV 2017
• dot27/temporal-tessellation
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A test video is processed by forming correspondences between its clips and the clips of reference videos with known semantics, following which, reference semantics can be transferred to the test video.
ACTION DETECTION VIDEO CAPTIONING VIDEO SUMMARIZATION VIDEO UNDERSTANDING
What does a Car-ssette tape tell?
This paper contributes a manually-annotated dataset on car scene, in extension to a previously published hospital audio captioning dataset.
Learnable Pooling Methods for Video Classification
• pomonam/LearnablePoolingMethods
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We demonstrate our solutions in the "The 2nd YouTube-8M Video Understanding Challenge", by using frame-level video and audio descriptors.