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Action Detection

61 papers with code · Computer Vision

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BMN: Boundary-Matching Network for Temporal Action Proposal Generation

ICCV 2019 PaddlePaddle/models

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.

ACTION DETECTION TEMPORAL ACTION PROPOSAL GENERATION

BSN: Boundary Sensitive Network for Temporal Action Proposal Generation

ECCV 2018 PaddlePaddle/models

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.

ACTION DETECTION TEMPORAL ACTION PROPOSAL GENERATION

A Multigrid Method for Efficiently Training Video Models

CVPR 2020 facebookresearch/SlowFast

We empirically demonstrate a general and robust grid schedule that yields a significant out-of-the-box training speedup without a loss in accuracy for different models (I3D, non-local, SlowFast), datasets (Kinetics, Something-Something, Charades), and training settings (with and without pre-training, 128 GPUs or 1 GPU).

ACTION DETECTION ACTION RECOGNITION VIDEO UNDERSTANDING

Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video Understanding

1 Nov 2019zhoubolei/moments_models

An event happening in the world is often made of different activities and actions that can unfold simultaneously or sequentially within a few seconds.

ACTION DETECTION ACTION RECOGNITION MULTI-LABEL LEARNING VIDEO UNDERSTANDING

An End-to-End Architecture for Keyword Spotting and Voice Activity Detection

28 Nov 2016mindorii/kws

We propose a single neural network architecture for two tasks: on-line keyword spotting and voice activity detection.

ACTION DETECTION ACTIVITY DETECTION KEYWORD SPOTTING

Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks

29 Aug 2016imatge-upc/activitynet-2016-cvprw

This thesis explore different approaches using Convolutional and Recurrent Neural Networks to classify and temporally localize activities on videos, furthermore an implementation to achieve it has been proposed.

ACTION DETECTION ACTIVITY DETECTION