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 801–850 of 1477 papers

TitleStatusHype
Spatio-Temporal Pyramid Graph Convolutions for Human Action Recognition and Postural Assessment—0
Spatiotemporal Pyramid Network for Video Action Recognition—0
Spatio-Temporal Vector of Locally Max Pooled Features for Action Recognition in Videos—0
Squeeze-and-Excitation on Spatial and Temporal Deep Feature Space for Action Recognition—0
SSAN: Separable Self-Attention Network for Video Representation Learning—0
SSNet: Scale Selection Network for Online 3D Action Prediction—0
Stacked Spatio-Temporal Graph Convolutional Networks for Action Segmentation—0
STAR-Net: Action Recognition using Spatio-Temporal Activation Reprojection—0
STAR-Transformer: A Spatio-temporal Cross Attention Transformer for Human Action Recognition—0
STAT: Towards Generalizable Temporal Action Localization—0
STM: SpatioTemporal and Motion Encoding for Action Recognition—0
Storyboard guided Alignment for Fine-grained Video Action Recognition—0
STSM: Spatio-Temporal Shift Module for Efficient Action Recognition—0
Sub-action Prototype Learning for Point-level Weakly-supervised Temporal Action Localization—0
Submission to ActivityNet Challenge 2019: Task B Spatio-temporal Action Localization—0
Submodular Attribute Selection for Action Recognition in Video—0
Summarization of User-Generated Sports Video by Using Deep Action Recognition Features—0
SurgPETL: Parameter-Efficient Image-to-Surgical-Video Transfer Learning for Surgical Phase Recognition—0
Survey of Action Recognition, Spotting and Spatio-Temporal Localization in Soccer -- Current Trends and Research Perspectives—0
SUSiNet: See, Understand and Summarize it—0
SVFormer: A Direct Training Spiking Transformer for Efficient Video Action Recognition—0
Symbiotic Graph Neural Networks for 3D Skeleton-based Human Action Recognition and Motion Prediction—0
Sympathy for the Details: Dense Trajectories and Hybrid Classification Architectures for Action Recognition—0
Table Tennis Stroke Detection and Recognition Using Ball Trajectory Data—0
TACo: Token-aware Cascade Contrastive Learning for Video-Text Alignment—0
TAN: Temporal Aggregation Network for Dense Multi-label Action Recognition—0
TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition—0
Temporal Action Localization by Structured Maximal Sums—0
Temporal Action Localization using Long Short-Term Dependency—0
Temporal Action Localization with Global Segmentation Mask Transformers—0
Temporal Action Localization with Multi-temporal Scales—0
Temporal Action Localization With Pyramid of Score Distribution Features—0
Temporal Action Localization with Variance-Aware Networks—0
Temporal Action Proposal Generation with Transformers—0
Temporal Attention-Augmented Graph Convolutional Network for Efficient Skeleton-Based Human Action Recognition—0
Temporal Bilinear Networks for Video Action Recognition—0
Temporal Contrastive Graph Learning for Video Action Recognition and Retrieval—0
Temporal Contrastive Learning with Curriculum—0
Temporal Convolution Based Action Proposal: Submission to ActivityNet 2017—0
Temporal-Distributed Backdoor Attack Against Video Based Action Recognition—0
Temporal Extension of Scale Pyramid and Spatial Pyramid Matching for Action Recognition—0
Temporal Fusion Network for Temporal Action Localization:Submission to ActivityNet Challenge 2020 (Task E)—0
Temporal-Guided Spiking Neural Networks for Event-Based Human Action Recognition—0
Temporal Hallucinating for Action Recognition With Few Still Images—0
Temporal Hockey Action Recognition via Pose and Optical Flows—0
Temporal Perceiving Video-Language Pre-training—0
Temporal Pyramid Pooling Based Convolutional Neural Networks for Action Recognition—0
Temporal Sequence Distillation: Towards Few-Frame Action Recognition in Videos—0
Temporal-Spatial Mapping for Action Recognition—0
Temporal Transformer Networks with Self-Supervision for 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