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 501–550 of 1477 papers

TitleStatusHype
A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling—0
Exploring Feature Representation and Training strategies in Temporal Action Localization—0
Exploring Temporal Context and Human Movement Dynamics for Online Action Detection in Videos—0
Exploring Temporal Preservation Networks for Precise Temporal Action Localization—0
Exploring Explainability in Video Action Recognition—0
Exploring Denoised Cross-Video Contrast for Weakly-Supervised Temporal Action Localization—0
Extending Temporal Data Augmentation for Video Action Recognition—0
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds—0
Exploiting the ConvLSTM: Human Action Recognition using Raw Depth Video-Based Recurrent Neural Networks—0
F4D: Factorized 4D Convolutional Neural Network for Efficient Video-level Representation Learning—0
A Generative Approach to Zero-Shot and Few-Shot Action Recognition—0
Action Recognition by Hierarchical Sequence Summarization—0
Exploiting Structure Sparsity for Covariance-based Visual Representation—0
Exploiting Spatial-Temporal Modelling and Multi-Modal Fusion for Human Action Recognition—0
Bridging the gap between Human Action Recognition and Online Action Detection—0
Exploiting Language Models for Visual Recognition—0
Exploiting deep residual networks for human action recognition from skeletal data—0
A Fine-to-Coarse Convolutional Neural Network for 3D Human Action Recognition—0
Expanded Parts Model for Human Attribute and Action Recognition in Still Images—0
Bridge the Gap: From Weak to Full Supervision for Temporal Action Localization with PseudoFormer—0
EXMOVES: Classifier-based Features for Scalable Action Recognition—0
Bregman Divergences for Infinite Dimensional Covariance Matrices—0
Action Recognition by Hierarchical Mid-level Action Elements—0
Evolution-Preserving Dense Trajectory Descriptors—0
Boundary Uncertainty in a Single-Stage Temporal Action Localization Network—0
Event-based Timestamp Image Encoding Network for Human Action Recognition and Anticipation—0
Adversarial Seeded Sequence Growing for Weakly-Supervised Temporal Action Localization—0
Event-based Action Recognition Using Timestamp Image Encoding Network—0
Evaluation of Color STIPs for Human Action Recognition—0
Boundary Content Graph Neural Network for Temporal Action Proposal Generation—0
Evaluating Transformers for Lightweight Action Recognition—0
Evaluating the Effectiveness of Automated Identity Masking (AIM) Methods with Human Perception and a Deep Convolutional Neural Network (CNN)—0
Boundary-Aware Proposal Generation Method for Temporal Action Localization—0
Action Recognition based on Subdivision-Fusion Model—0
A Compact Kernel Approximation for 3D Action Recognition—0
3DFCNN: Real-Time Action Recognition using 3D Deep Neural Networks with Raw Depth Information—0
Equivalent Classification Mapping for Weakly Supervised Temporal Action Localization—0
Boosting Semi-Supervised Temporal Action Localization by Learning from Non-Target Classes—0
Ensembles of Deep Neural Networks for Action Recognition in Still Images—0
Ensemble One-dimensional Convolution Neural Networks for Skeleton-based Action Recognition—0
Boosting Point-Supervised Temporal Action Localization through Integrating Query Reformation and Optimal Transport—0
Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers—0
Enhanced Spatiotemporal Prediction Using Physical-guided And Frequency-enhanced Recurrent Neural Networks—0
Enhanced skeleton visualization for view invariant human action recognition—0
Body Joint guided 3D Deep Convolutional Descriptors for Action Recognition—0
End-to-End Joint Semantic Segmentation of Actors and Actions in Video—0
BLP -- Boundary Likelihood Pinpointing Networks for Accurate Temporal Action Localization—0
Adversarial Attack on Skeleton-based Human Action Recognition—0
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks—0
Enabling Weakly-Supervised Temporal Action Localization from On-Device Learning of the Video Stream—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