Temporal Action Localization Edit Task
Computer Vision • Action Localization
About
Temporal Action Localization aims to detect activities in the video stream and output beginning and end timestamps. It is closely related to Temporal Action Proposal Generation.
Benchmarks
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Subtasks
Datasets
Greatest papers with code
MoViNets: Mobile Video Networks for Efficient Video Recognition
We present Mobile Video Networks (MoViNets), a family of computation and memory efficient video networks that can operate on streaming video for online inference.
Ranked #1 on
Action Classification
on Moments in Time
ACTION CLASSIFICATION ACTION RECOGNITION NEURAL ARCHITECTURE SEARCH VIDEO RECOGNITION
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.
Ranked #2 on
Temporal Action Localization
on J-HMDB-21
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
A Closer Look at Spatiotemporal Convolutions for Action Recognition
CVPR 2018
• microsoft/computervision-recipes
•
In this paper we discuss several forms of spatiotemporal convolutions for video analysis and study their effects on action recognition.
Ranked #4 on
Action Recognition
on Sports-1M
BMN: Boundary-Matching Network for Temporal Action Proposal Generation
To address these difficulties, we introduce the Boundary-Matching (BM) mechanism to evaluate confidence scores of densely distributed proposals, which denote a proposal as a matching pair of starting and ending boundaries and combine all densely distributed BM pairs into the BM confidence map.
Ranked #1 on
Action Recognition
on THUMOS’14
ACTION DETECTION ACTION RECOGNITION TEMPORAL ACTION PROPOSAL GENERATION
BSN: Boundary Sensitive Network for Temporal Action Proposal Generation
Temporal action proposal generation is an important yet challenging problem, since temporal proposals with rich action content are indispensable for analysing real-world videos with long duration and high proportion irrelevant content.
Ranked #1 on
Temporal Action Proposal Generation
on THUMOS' 14
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
Dynamics of human body skeletons convey significant information for human action recognition.
Ranked #2 on
Action Recognition
on IRD
3D HUMAN POSE ESTIMATION ACTION RECOGNITION MULTIMODAL ACTIVITY RECOGNITION SKELETON BASED ACTION RECOGNITION
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks
Over the last decade, Convolutional Neural Network (CNN) models have been highly successful in solving complex vision problems.
3D ACTION RECOGNITION KNOWLEDGE DISTILLATION OBJECT LOCALIZATION
Temporal Segment Networks for Action Recognition in Videos
Furthermore, based on the temporal segment networks, we won the video classification track at the ActivityNet challenge 2016 among 24 teams, which demonstrates the effectiveness of TSN and the proposed good practices.
Ranked #11 on
Action Classification
on Moments in Time
(Top 5 Accuracy metric)
ACTION CLASSIFICATION ACTION RECOGNITION ACTION RECOGNITION IN VIDEOS ACTION RECOGNITION IN VIDEOS
Sparse 3D convolutional neural networks
• facebookresearch/SparseConvNet
•
We have implemented a convolutional neural network designed for processing sparse three-dimensional input data.