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 351–375 of 455 papers

Title	Date	Tasks	Status	Hype
Learnable Pooling Methods for Video Classification	Oct 1, 2018	ClassificationGeneral Classification	CodeCode Available	0
Non-local NetVLAD Encoding for Video Classification	Sep 29, 2018	ClassificationGeneral Classification	—Unverified	0
Rate-Accuracy Trade-Off In Video Classification With Deep Convolutional Neural Networks	Sep 27, 2018	Action RecognitionClassification	CodeCode Available	0
Large-Scale Video Classification with Feature Space Augmentation coupled with Learned Label Relations and Ensembling	Sep 21, 2018	General ClassificationVideo Classification	—Unverified	0
Towards Good Practices for Multi-modal Fusion in Large-scale Video Classification	Sep 16, 2018	ClassificationGeneral Classification	—Unverified	0
Label Denoising with Large Ensembles of Heterogeneous Neural Networks	Sep 12, 2018	Data AugmentationDenoising	—Unverified	0
Compound Memory Networks for Few-shot Video Classification	Sep 1, 2018	ClassificationGeneral Classification	—Unverified	0
Approach for Video Classification with Multi-label on YouTube-8M Dataset	Aug 27, 2018	General ClassificationVideo Classification	—Unverified	0
Isometric Transformation Invariant Graph-based Deep Neural Network	Aug 21, 2018	General ClassificationTranslation	—Unverified	0
Improving Spatiotemporal Self-Supervision by Deep Reinforcement Learning	Jul 30, 2018	Deep Reinforcement LearningGeneral Classification	—Unverified	0
Towards Automatic Speech Identification from Vocal Tract Shape Dynamics in Real-time MRI	Jul 29, 2018	Action RecognitionClassification	—Unverified	0
Multimodal Classification with Deep Convolutional-Recurrent Neural Networks for Electroencephalography	Jul 24, 2018	Brain Computer InterfaceClassification	—Unverified	0
Deep Discriminative Model for Video Classification	Jul 22, 2018	Action RecognitionClassification	—Unverified	0
Deep Architectures and Ensembles for Semantic Video Classification	Jul 3, 2018	ClassificationDiversity	—Unverified	0
Adversarial Perturbations Against Real-Time Video Classification Systems	Jul 2, 2018	ClassificationGeneral Classification	CodeCode Available	0
A convex method for classification of groups of examples	Jun 21, 2018	ClassificationGeneral Classification	—Unverified	0
I Have Seen Enough: A Teacher Student Network for Video Classification Using Fewer Frames	May 12, 2018	ClassificationGeneral Classification	—Unverified	0
Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph Distillation for Video Classification	Apr 26, 2018	ClassificationGeneral Classification	—Unverified	0
Visual Data Synthesis via GAN for Zero-Shot Video Classification	Apr 26, 2018	ClassificationGeneral Classification	—Unverified	0
Charades-Ego: A Large-Scale Dataset of Paired Third and First Person Videos	Apr 25, 2018	General ClassificationVideo Classification	—Unverified	0
On the effectiveness of task granularity for transfer learning	Apr 24, 2018	ClassificationDiversity	CodeCode Available	1
ECO: Efficient Convolutional Network for Online Video Understanding	Apr 24, 2018	Action ClassificationAction Recognition	CodeCode Available	0
Walk-Steered Convolution for Graph Classification	Apr 16, 2018	ClassificationClustering	—Unverified	0
Fine-grained Activity Recognition in Baseball Videos	Apr 9, 2018	Action DetectionActivity Detection	CodeCode Available	0
Group Normalization	Mar 22, 2018	Objectobject-detection	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