Action Recognition

Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.

In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.

Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.

Papers

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Showing 2661–2670 of 2759 papers

Title	Date	Tasks	Status
Multi-Feature Max-Margin Hierarchical Bayesian Model for Action Recognition	Jun 1, 2015	Action RecognitionGeneral Classification	—Unverified
What do 15,000 Object Categories Tell Us About Classifying and Localizing Actions?	Jun 1, 2015	Action ClassificationAction Recognition	—Unverified
Action Recognition with Trajectory-Pooled Deep-Convolutional Descriptors	May 19, 2015	Action RecognitionAction Understanding	CodeCode Available
The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition	May 17, 2015	Action RecognitionMulti-class Classification	—Unverified
Contextual Action Recognition with R*CNN	May 5, 2015	Action RecognitionAttribute	CodeCode Available
Modeling Representation of Videos for Anomaly Detection using Deep Learning: A Review	May 4, 2015	Action RecognitionAnomaly Detection	—Unverified
Fusing multiple features for depth-based action recognition	May 1, 2015	3D Action RecognitionAction Recognition	—Unverified
Differential Recurrent Neural Networks for Action Recognition	Apr 25, 2015	Action RecognitionTemporal Action Localization	—Unverified
A robust and efficient video representation for action recognition	Apr 21, 2015	Action RecognitionHomography Estimation	—Unverified
Learning discriminative trajectorylet detector sets for accurate skeleton-based action recognition	Apr 20, 2015	Action RecognitionSkeleton Based Action Recognition	—Unverified

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All datasets Something-Something V2 UCF101 HMDB-51 Something-Something V1 AVA v2.2 EPIC-KITCHENS-100 NTU RGB+D NTU RGB+D 120 Diving-48 ActivityNet AVA v2.1 H2O (2 Hands and Objects)

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MViTv2-B (IN-21K + Kinetics400 pretrain)	Top-5 Accuracy	93.4	—	Unverified
2	RSANet-R50 (8+16 frames, ImageNet pretrained, 2 clips)	Top-5 Accuracy	91.1	—	Unverified
3	MVD (Kinetics400 pretrain, ViT-H, 16 frame)	Top-1 Accuracy	77.3	—	Unverified
4	InternVideo	Top-1 Accuracy	77.2	—	Unverified
5	DejaVid	Top-1 Accuracy	77.2	—	Unverified
6	InternVideo2-1B	Top-1 Accuracy	77.1	—	Unverified
7	VideoMAE V2-g	Top-1 Accuracy	77	—	Unverified
8	MVD (Kinetics400 pretrain, ViT-L, 16 frame)	Top-1 Accuracy	76.7	—	Unverified
9	Hiera-L (no extra data)	Top-1 Accuracy	76.5	—	Unverified
10	TubeViT-L	Top-1 Accuracy	76.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FTP-UniFormerV2-L/14	3-fold Accuracy	99.7	—	Unverified
2	OmniVec2	3-fold Accuracy	99.6	—	Unverified
3	OmniVec	3-fold Accuracy	99.6	—	Unverified
4	VideoMAE V2-g	3-fold Accuracy	99.6	—	Unverified
5	BIKE	3-fold Accuracy	98.8	—	Unverified
6	SMART	3-fold Accuracy	98.64	—	Unverified
7	ZeroI2V ViT-L/14	3-fold Accuracy	98.6	—	Unverified
8	OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)	3-fold Accuracy	98.6	—	Unverified
9	PERF-Net (multi-distilled S3D)	3-fold Accuracy	98.6	—	Unverified
10	Text4Vis	3-fold Accuracy	98.2	—	Unverified