Video Classification

Video Classification is the task of producing a label that is relevant to the video given its frames. A good video level classifier is one that not only provides accurate frame labels, but also best describes the entire video given the features and the annotations of the various frames in the video. For example, a video might contain a tree in some frame, but the label that is central to the video might be something else (e.g., “hiking”). The granularity of the labels that are needed to describe the frames and the video depends on the task. Typical tasks include assigning one or more global labels to the video, and assigning one or more labels for each frame inside the video.

Source: Efficient Large Scale Video Classification

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 426–450 of 455 papers

Title	Date	Tasks	Status	Hype
Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition	Aug 25, 2016	Action RecognitionAction Recognition In Videos	—Unverified	0
Discriminatively Trained Latent Ordinal Model for Video Classification	Aug 8, 2016	Action RecognitionClassification	—Unverified	0
Analyzing Linear Dynamical Systems: From Modeling to Coding and Learning	Aug 3, 2016	Dictionary LearningGeneral Classification	CodeCode Available	0
CUHK & ETHZ & SIAT Submission to ActivityNet Challenge 2016	Aug 2, 2016	General ClassificationVideo Classification	CodeCode Available	0
Untrimmed Video Classification for Activity Detection: submission to ActivityNet Challenge	Jul 7, 2016	Action DetectionActivity Detection	CodeCode Available	0
Harnessing Object and Scene Semantics for Large-Scale Video Understanding	Jun 1, 2016	Action RecognitionClustering	—Unverified	0
Sparse Coding and Dictionary Learning With Linear Dynamical Systems	Jun 1, 2016	Dictionary LearningVideo Classification	—Unverified	0
Evolution of active categorical image classification via saccadic eye movement	Mar 27, 2016	ClassificationGeneral Classification	—Unverified	0
Modelling Temporal Information Using Discrete Fourier Transform for Video Classification	Mar 20, 2016	Action RecognitionClassification	—Unverified	0
Labeling the Features Not the Samples: Efficient Video Classification with Minimal Supervision	Dec 1, 2015	Clusteringfeature selection	—Unverified	0
Deep End2End Voxel2Voxel Prediction	Nov 20, 2015	Neural Architecture SearchOptical Flow Estimation	—Unverified	0
Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks	Nov 19, 2015	EEGElectroencephalogram (EEG)	CodeCode Available	0
Handcrafted Local Features are Convolutional Neural Networks	Nov 16, 2015	Action RecognitionOptical Flow Estimation	—Unverified	0
Fusing Multi-Stream Deep Networks for Video Classification	Sep 21, 2015	ClassificationGeneral Classification	—Unverified	0
Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video	Jun 5, 2015	Gesture RecognitionImage Captioning	CodeCode Available	0
ActivityNet: A Large-Scale Video Benchmark for Human Activity Understanding	Jun 1, 2015	Action DetectionAction Recognition	CodeCode Available	0
Efficient Large Scale Video Classification	May 22, 2015	ClassificationGeneral Classification	—Unverified	0
Evaluating Two-Stream CNN for Video Classification	Apr 8, 2015	ClassificationGeneral Classification	—Unverified	0
Modeling Spatial-Temporal Clues in a Hybrid Deep Learning Framework for Video Classification	Apr 7, 2015	ClassificationGeneral Classification	CodeCode Available	0
Beyond Short Snippets: Deep Networks for Video Classification	Mar 31, 2015	Action RecognitionClassification	CodeCode Available	0
Video-Based Action Recognition Using Rate-Invariant Analysis of Covariance Trajectories	Mar 23, 2015	Action RecognitionGeneral Classification	—Unverified	0
Exploiting Image-trained CNN Architectures for Unconstrained Video Classification	Mar 13, 2015	ClassificationEvent Detection	—Unverified	0
Long-short Term Motion Feature for Action Classification and Retrieval	Feb 13, 2015	Action ClassificationClassification	—Unverified	0
Large-Scale Video Classification with Convolutional Neural Networks	Jun 23, 2014	Action RecognitionClassification	CodeCode Available	1
Two-Stream Convolutional Networks for Action Recognition in Videos	Jun 9, 2014	Action ClassificationAction Recognition	CodeCode Available	0

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All datasets Breakfast COIN MoB YouTube-8M Hockey Fight Detection Dataset Charades Home Action Genome Kinetics Multimodal PISA Something-Something V1 Something-Something V2 SRI-APPROVE Fine-Grained Video Classification

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	HERMES	Accuracy (%)	95.2	—	Unverified
2	MA-LMM	Accuracy (%)	93	—	Unverified
3	S5	Accuracy (%)	90.7	—	Unverified
4	TranS4mer	Accuracy (%)	90.27	—	Unverified
5	D-Sprv.	Accuracy (%)	89.9	—	Unverified
6	ViS4mer	Accuracy (%)	88.2	—	Unverified
7	GHRM	Accuracy (%)	75.5	—	Unverified
8	Timeception	Accuracy (%)	71.3	—	Unverified
9	VideoGraph	Accuracy (%)	69.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HERMES	Accuracy (%)	93.5	—	Unverified
2	MA-LMM	Accuracy (%)	93.2	—	Unverified
3	S5	Accuracy (%)	90.8	—	Unverified
4	D-Sprv.	Accuracy (%)	90	—	Unverified
5	TranS4mer	Accuracy (%)	89.3	—	Unverified
6	ViS4mer	Accuracy (%)	88.4	—	Unverified
7	TSN	Accuracy (%)	73.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	VTN	Accuracy	77.85	—	Unverified
2	I3D	Accuracy	72.11	—	Unverified
3	ConvLSTM	Accuracy	69.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DCGN (self-attention graph pooling)	Hit@1	87.7	—	Unverified
2	Hierarchical LSTM with MoE	Hit@1	86.8	—	Unverified
3	Mixture-of-2-Experts	Hit@1	70.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Structured Keypoint Pooling	Accuracy	99.5	—	Unverified
2	CNN+LSTM	1:1 Accuracy	98	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Multigrid	mAP	38.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Cooperative Ours (3rd-person)	Accuracy (%)	24.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Multigrid	Top-1	77.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Video	Accuracy (%)	73.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MSNet-R50En (ours)	Top-5 Accuracy	84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MSNet-R50En (ours)	Top-5 Accuracy	91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Multi-Label Prototypes Contrastive Learning	AUPR	88.4	—	Unverified