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

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Showing 551–600 of 1477 papers

TitleStatusHype
Continuous Human Action Recognition for Human-Machine Interaction: A Review—0
A New Action Recognition Framework for Video Highlights Summarization in Sporting Events—0
Continuous Action Recognition Based on Sequence Alignment—0
An End-to-End Two-Stream Network Based on RGB Flow and Representation Flow for Human Action Recognition—0
Action Recognition with Image Based CNN Features—0
Human Action Recognition from Various Data Modalities: A Review—0
An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data—0
Context-LSTM: a robust classifier for video detection on UCF101—0
Action4D: Real-time Action Recognition in the Crowd and Clutter—0
Context-based Object Viewpoint Estimation: A 2D Relational Approach—0
Context Aware Graph Convolution for Skeleton-Based Action Recognition—0
End-to-End Video Captioning—0
2D versus 3D Convolutional Spiking Neural Networks Trained with Unsupervised STDP for Human Action Recognition—0
Human Action Recognition (HAR) Using Skeleton-based Spatial Temporal Relative Transformer Network: ST-RTR—0
Human Action Recognition: Pose-based Attention draws focus to Hands—0
Context-Aware Cross-Attention for Skeleton-Based Human Action Recognition—0
Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion—0
Concurrence-Aware Long Short-Term Sub-Memories for Person-Person Action Recognition—0
Action4D: Online Action Recognition in the Crowd and Clutter—0
Human Action Recognition Based on Context-Dependent Graph Kernels—0
Human Action Recognition Across Datasets by Foreground-weighted Histogram Decomposition—0
An Attention Enhanced Graph Convolutional LSTM Network for Skeleton-Based Action Recognition—0
Human Action Recognition and Assessment via Deep Neural Network Self-Organization—0
Action Recognition via Pose-Based Graph Convolutional Networks with Intermediate Dense Supervision—0
An Approach to Pose-Based Action Recognition—0
Human Action Performance using Deep Neuro-Fuzzy Recurrent Attention Model—0
Human Action Recognition and Prediction: A Survey—0
Human Action Recognition Based on Multi-scale Feature Maps from Depth Video Sequences—0
An Analysis of Action Recognition Datasets for Language and Vision Tasks—0
GTA: Global Temporal Attention for Video Action Understanding—0
Complex Video Action Reasoning via Learnable Markov Logic Network—0
Human Action Adverb Recognition: ADHA Dataset and A Three-Stream Hybrid Model—0
Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks—0
Group sparsity and geometry constrained dictionary learning for action recognition from depth maps.—0
Group-Skeleton-Based Human Action Recognition in Complex Events—0
Complex Human Action Recognition in Live Videos Using Hybrid FR-DL Method—0
Action2Vec: A Crossmodal Embedding Approach to Action Learning—0
GTM: Gray Temporal Model for Video Recognition—0
HabitAction: A Video Dataset for Human Habitual Behavior Recognition—0
Composable Augmentation Encoding for Video Representation Learning—0
Hand Action Detection from Ego-centric Depth Sequences with Error-correcting Hough Transform—0
Handcrafted Local Features are Convolutional Neural Networks—0
Handcrafted localized phase features for human action recognition—0
Hand-Object Interaction and Precise Localization in Transitive Action Recognition—0
Compressed Video Action Recognition with Refined Motion Vector—0
Human Action Attribute Learning From Video Data Using Low-Rank Representations—0
GraSens: A Gabor Residual Anti-aliasing Sensing Framework for Action Recognition using WiFi—0
Harnessing Object and Scene Semantics for Large-Scale Video Understanding—0
Harnessing the Deep Net Object Models for Enhancing Human Action Recognition—0
Graph Edge Convolutional Neural Networks for Skeleton Based Action Recognition—0
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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