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 61–70 of 124 papers

Title	Date	Tasks	Status
Towards Efficient Coarse-to-Fine Networks for Action and Gesture Recognition	Aug 1, 2020	3D Action RecognitionAction Classification	—Unverified
Self-Supervised MultiModal Versatile Networks	Jun 29, 2020	Action Recognition In VideosAudio Classification	CodeCode Available
Dynamic Sampling Networks for Efficient Action Recognition in Videos	Jun 28, 2020	Action RecognitionAction Recognition In Videos	—Unverified
Learn to cycle: Time-consistent feature discovery for action recognition	Jun 15, 2020	Action ClassificationAction Recognition	CodeCode Available
Spatiotemporal Fusion in 3D CNNs: A Probabilistic View	Apr 10, 2020	Action RecognitionAction Recognition In Videos	—Unverified
Dynamic Inference: A New Approach Toward Efficient Video Action Recognition	Feb 9, 2020	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
Skeleton based Activity Recognition by Fusing Part-wise Spatio-temporal and Attention Driven Residues	Dec 2, 2019	3D Action RecognitionAction Recognition	—Unverified
Gating Revisited: Deep Multi-layer RNNs That Can Be Trained	Nov 25, 2019	Action RecognitionAction Recognition In Videos	CodeCode Available
Deep Image-to-Video Adaptation and Fusion Networks for Action Recognition	Nov 25, 2019	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	MMNet	X-Sub	97.4	—	Unverified
2	DSCNet (RGB + Pose)	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)	mAP@0.1	54.5	—	Unverified
2	Single-stream R-C3D (one-way buffer)	mAP@0.1	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