SOTAVerified

Temporal Action Localization

Temporal Action Localization aims to detect activities in the video stream and output beginning and end timestamps. It is closely related to Temporal Action Proposal Generation.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1051–1100 of 1477 papers

TitleStatusHype
Active Learning with Effective Scoring Functions for Semi-Supervised Temporal Action Localization—0
Activity Graph Transformer for Temporal Action Localization—0
Activity Recognition on a Large Scale in Short Videos - Moments in Time Dataset—0
Actor-Centric Relation Network—0
Towards Weakly Supervised End-to-end Learning for Long-video Action Recognition—0
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition—0
Adaptive Down-Sampling and Dimension Reduction in Time Elastic Kernel Machines for Efficient Recognition of Isolated Gestures—0
Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action Recognition with Virtual Connections—0
Adaptive Mutual Supervision for Weakly-Supervised Temporal Action Localization—0
Adaptive Perception Transformer for Temporal Action Localization—0
Adaptive RNN Tree for Large-Scale Human Action Recognition—0
AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos—0
Adding Attentiveness to the Neurons in Recurrent Neural Networks—0
A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data—0
A discussion on the validation tests employed to compare human action recognition methods using the MSR Action3D dataset—0
ADM-Loc: Actionness Distribution Modeling for Point-supervised Temporal Action Localization—0
Advances in Human Action Recognition: A Survey—0
Adversarial Attack on Skeleton-based Human Action Recognition—0
Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers—0
Adversarial Seeded Sequence Growing for Weakly-Supervised Temporal Action Localization—0
A Fine-to-Coarse Convolutional Neural Network for 3D Human Action Recognition—0
A Generative Approach to Zero-Shot and Few-Shot Action Recognition—0
A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling—0
A Grid-based Representation for Human Action Recognition—0
A Hierarchical Pose-Based Approach to Complex Action Understanding Using Dictionaries of Actionlets and Motion Poselets—0
A Hybrid Framework for Action Recognition in Low-Quality Video Sequences—0
A Hybrid Loss for Multiclass and Structured Prediction—0
A Key Volume Mining Deep Framework for Action Recognition—0
A Large-Scale Re-identification Analysis in Sporting Scenarios: the Betrayal of Reaching a Critical Point—0
A Large-Scale Robustness Analysis of Video Action Recognition Models—0
A Large-scale Varying-view RGB-D Action Dataset for Arbitrary-view Human Action Recognition—0
A Latent Clothing Attribute Approach for Human Pose Estimation—0
Align before Adapt: Leveraging Entity-to-Region Alignments for Generalizable Video Action Recognition—0
Alignment-guided Temporal Attention for Video Action Recognition—0
Alternative Semantic Representations for Zero-Shot Human Action Recognition—0
A Multi-Stream Bi-Directional Recurrent Neural Network for Fine-Grained Action Detection—0
Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks—0
An Analysis of Action Recognition Datasets for Language and Vision Tasks—0
An Approach to Pose-Based Action Recognition—0
An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition—0
End-to-End Video Captioning—0
An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data—0
An End-to-End Two-Stream Network Based on RGB Flow and Representation Flow for Human Action Recognition—0
A New Action Recognition Framework for Video Highlights Summarization in Sporting Events—0
A New Representation of Skeleton Sequences for 3D Action Recognition—0
An Improved Video Analysis using Context based Extension of LSH—0
An Information-rich Sampling Technique over Spatio-Temporal CNN for Classification of Human Actions in Videos—0
Annotation-Efficient Untrimmed Video Action Recognition—0
Annotation Methodologies for Vision and Language Dataset Creation—0
A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis—0
Show:102550
← PrevPage 22 of 30Next →
All datasetsTHUMOS14ActivityNet-1.3HACSFineActionMultiTHUMOSCrossTaskEPIC-KITCHENS-100MUSESActivityNet-1.2Ego4D MQ testEgo4D MQ valMEXaction2

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AdaTAD (VideoMAEv2-giant)Avg mAP (0.3:0.7)76.9—Unverified
2RDFA-S6 (InternVideo2-6B)Avg mAP (0.3:0.7)74.2—Unverified
3ActionMamba(InternVideo2-6B)Avg mAP (0.3:0.7)72.72—Unverified
4GCMmAP IOU@0.172.5—Unverified
5AGT (Ours)mAP IOU@0.172.1—Unverified
6InternVideo2-6BAvg mAP (0.3:0.7)72—Unverified
7ActionFormer (InternVideo features)Avg mAP (0.3:0.7)71.58—Unverified
8TriDet (VideoMAE v2-g feature)Avg mAP (0.3:0.7)70.1—Unverified
9InternVideo2-1BAvg mAP (0.3:0.7)69.8—Unverified
10ActionFormer (VideoMAE V2-g features)Avg mAP (0.3:0.7)69.6—Unverified
#ModelMetricClaimedVerifiedStatus
1UnLoc-LmAP IOU@0.559.3—Unverified
2RDFA-S6 (InternVideo2-6B)mAP42.9—Unverified
3ActionMamba (InternVideo2-6B)mAP42.02—Unverified
4PRN+BMN (ensemble)mAP42—Unverified
5AdaTAD (VideoMAEv2-giant)mAP41.93—Unverified
6InternVideo2-6BmAP41.2—Unverified
7InternVideo2-1BmAP40.4—Unverified
8UniMD+Sync.mAP39.83—Unverified
9PRN (CSN)mAP39.4—Unverified
10InternVideomAP39—Unverified
#ModelMetricClaimedVerifiedStatus
1RDFA-S6 (InternVideo2-6B)Average-mAP45.8—Unverified
2ActionMamba(InternVideo2-6B)Average-mAP44.56—Unverified
3DyFADet(VideoMAEv2)Average-mAP44.3—Unverified
4InternVideo2-6BAverage-mAP43.3—Unverified
5TriDet (VideoMAEv2)Average-mAP43.1—Unverified
6InternVideo2-1BAverage-mAP42.4—Unverified
7InternVideoAverage-mAP41.55—Unverified
8TriDet (SlowFast)Average-mAP38.6—Unverified
9TriDet (I3D RGB)Average-mAP36.8—Unverified
10TadTr (I3D RGB)Average-mAP32.09—Unverified
#ModelMetricClaimedVerifiedStatus
1RDFA-S6 (InternVideo2-6B)mAP29.6—Unverified
2ActionMamba(InternVideo2-6B)mAP29.04—Unverified
3InternVideo2-6BmAP27.7—Unverified
4DyFADet (VideoMAE v2-g)mAP23.8—Unverified
5VideoMAE V2-gmAP18.24—Unverified
6InternVideomAP17.57—Unverified
7BMN (i3d feaure)mAP9.25—Unverified
8G-TAD (i3d feature)mAP9.06—Unverified
9DBG (i3d feature)mAP6.75—Unverified
#ModelMetricClaimedVerifiedStatus
1TriDet (VideoMAEv2)Average mAP37.5—Unverified
2DualDETR (I3D-rgb)Average mAP32.64—Unverified
3TriDet (I3D-rgb)Average mAP30.7—Unverified
4TemporalMaxerAverage mAP29.9—Unverified
5PointTADAverage mAP23.5—Unverified
6PDANAverage mAP17.3—Unverified
7MS-TCTAverage mAP16.2—Unverified
8MLADAverage mAP14.2—Unverified
#ModelMetricClaimedVerifiedStatus
1VideoCLIPRecall47.3—Unverified
2VLMRecall46.5—Unverified
3TACoRecall42.5—Unverified
4Text-Video EmbeddingRecall33.6—Unverified
5Fully-supervised upper-boundRecall31.6—Unverified
6ZhukovRecall22.4—Unverified
7AlayracRecall13.3—Unverified
#ModelMetricClaimedVerifiedStatus
1AdaTAD (verb, VideoMAE-L)Avg mAP (0.1-0.5)29.3—Unverified
2TriDet (verb)Avg mAP (0.1-0.5)25.4—Unverified
3TemporalMaxer (verb)Avg mAP (0.1-0.5)24.5—Unverified
4ActionFormer (verb)Avg mAP (0.1-0.5)23.5—Unverified
5G-TAD (verb)Avg mAP (0.1-0.5)9.4—Unverified
6BMN (verb)Avg mAP (0.1-0.5)8.4—Unverified
#ModelMetricClaimedVerifiedStatus
1TemporalMaxermAP27.2—Unverified
2MUSESmAP18.6—Unverified
#ModelMetricClaimedVerifiedStatus
1DeepMetricLearnermAP IOU@0.535.2—Unverified
#ModelMetricClaimedVerifiedStatus
1ActionFormer (SlowFast+Omnivore+EgoVLP)Average mAP21.76—Unverified
#ModelMetricClaimedVerifiedStatus
1ActionFormer (SlowFast+Omnivore+EgoVLP)Average mAP21.4—Unverified
#ModelMetricClaimedVerifiedStatus
1S-CNNmAP7.4—Unverified