Action Recognition In Videos

Action Recognition in Videos is a task in computer vision and pattern recognition where the goal is to identify and categorize human actions performed in a video sequence. The task involves analyzing the spatiotemporal dynamics of the actions and mapping them to a predefined set of action classes, such as running, jumping, or swimming.

Papers

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Showing 101–110 of 124 papers

Title	Date	Tasks	Status
Temporal Sequence Distillation: Towards Few-Frame Action Recognition in Videos	Aug 15, 2018	Action RecognitionAction Recognition In Videos	—Unverified
An Information-rich Sampling Technique over Spatio-Temporal CNN for Classification of Human Actions in Videos	Feb 6, 2020	Action RecognitionAction Recognition In Videos	—Unverified
The impact of Compositionality in Zero-shot Multi-label action recognition for Object-based tasks	May 14, 2024	Action RecognitionAction Recognition In Videos	—Unverified
Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition	Dec 14, 2017	Action RecognitionAction Recognition In Videos	—Unverified
Learning to Recognize 3D Human Action from A New Skeleton-based Representation Using Deep Convolutional Neural Networks	Dec 26, 2018	3D Action RecognitionAction Recognition	—Unverified
Learning Transferable Self-attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision	Feb 20, 2019	Action RecognitionAction Recognition In Videos	—Unverified
Top-down Attention Recurrent VLAD Encoding for Action Recognition in Videos	Aug 29, 2018	Action RecognitionAction Recognition In Videos	—Unverified
Toward Accurate Person-level Action Recognition in Videos of Crowded Scenes	Oct 16, 2020	Action RecognitionAction Recognition In Videos	—Unverified
Developing the Path Signature Methodology and its Application to Landmark-based Human Action Recognition	Jul 13, 2017	Action ClassificationAction Recognition	—Unverified
Knowledge Prompting for Few-shot Action Recognition	Nov 22, 2022	Action RecognitionAction Recognition In Videos	—Unverified

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All datasets Jester (Gesture Recognition)PKU-MMD UCF101 Something-Something V2 Kinetics 400 AVA v2.2 FS-Something-Something V2-Full FS-Something-Something V2-Small Sports-1M THUMOS14 ActivityNet AVA v2.1

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	CPNet Res34, 5 CP	Val	96.7	—	Unverified
2	STM (Resnet-50, 16 frames)	Val	96.7	—	Unverified
3	MFNet	Val	96.68	—	Unverified
4	DIN	Val	95.31	—	Unverified
5	MultiScale TRN	Val	95.31	—	Unverified
6	convSTAR	Val	92.7	—	Unverified
7	3D-SqueezeNet	Val	90.77	—	Unverified
8	3D-ShuffleNetV2 0.25x	Val	86.91	—	Unverified
9	3D-MobileNetV2 0.2x	Val	86.43	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DSCNet (RGB + Pose)	X-Sub	97.4	—	Unverified
2	MMNet	X-Sub	97.4	—	Unverified
3	EPAM-Net	X-Sub	96.2	—	Unverified
4	DVANet (RGB only)	X-Sub	95.8	—	Unverified
5	TSMF	X-Sub	95.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STM (ImageNet+Kinetics pretrain)	3-fold Accuracy	96.2	—	Unverified
2	3D-SqueezeNet	3-fold Accuracy	74.94	—	Unverified
3	3D-ShuffleNetV2 0.25x	3-fold Accuracy	56.52	—	Unverified
4	3D-MobileNetV2 0.2x	3-fold Accuracy	55.56	—	Unverified
5	Baseline UCF101	3-fold Accuracy	43.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STM (16 frames, ImageNet pretraining)	Top-1 Accuracy	64.2	—	Unverified
2	CPNet Res34, 5 CP	Top-1 Accuracy	57.65	—	Unverified
3	2-Stream TRN	Top-1 Accuracy	55.52	—	Unverified
4	DIN	Top-1 Accuracy	34.11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Florence	Top-1 Accuracy	86.5	—	Unverified
2	ActionCLIP (ViT-B/16)	Top-1 Accuracy	83.8	—	Unverified
3	Frozen Backbone, SwinV2-G-ext22K (Video-Swin)	Top-1 Accuracy	81.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	YOWO+LFB*	mAP (Val)	20.2	—	Unverified
2	VideoMAE V2	mAP (Val)	18.24	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ITANet	Top-1 Accuracy(5-Way-1-Shot)	49.2	—	Unverified
2	OTAM[3]++	Top-1 Accuracy(5-Way-1-Shot)	42.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ITANet	Top-1 Accuracy(5-Way-1-Shot)	39.8	—	Unverified
2	CMN[35]	Top-1 Accuracy(5-Way-1-Shot)	36.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	G-Blend	Video hit@1	74.8	—	Unverified
2	LSTM +Pretrained on YT-8M	Video hit@1	65.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Single-stream R-C3D (two-way buffer)	[email protected]	54.5	—	Unverified
2	Single-stream R-C3D (one-way buffer)	[email protected]	51.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LSTM + Pretrained on YT-8M	mAP	75.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	YOWO+LFB*	mAP (Val)	19.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STM (ImageNet+Kinetics pretrain)	Average accuracy of 3 splits	72.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Florence	Top-1 Accuracy	87.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	G-Blend	Clip Hit@1	49.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	2D-3D-Softargmax (RGB only)	Accuracy (CS)	85.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	STM (16 frames, ImageNet pretraining)	Top 1 Accuracy	50.7	—	Unverified