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 451–500 of 1477 papers

TitleStatusHype
From CNNs to Transformers in Multimodal Human Action Recognition: A Survey—0
Efficient Temporal Sequence Comparison and Classification Using Gram Matrix Embeddings on a Riemannian Manifold—0
Egocentric Hand Detection Via Dynamic Region Growing—0
Egocentric Hand Track and Object-based Human Action Recognition—0
From Pose to Activity: Surveying Datasets and Introducing CONVERSE—0
EgoPCA: A New Framework for Egocentric Hand-Object Interaction Understanding—0
Eigen Evolution Pooling for Human Action Recognition—0
Elastic Functional Coding of Human Actions: From Vector-Fields to Latent Variables—0
ElderSim: A Synthetic Data Generation Platform for Human Action Recognition in Eldercare Applications—0
Bio-Inspired Human Action Recognition using Hybrid Max-Product Neuro-Fuzzy Classifier and Quantum-Behaved PSO—0
Emotion-Based Crowd Representation for Abnormality Detection—0
Enabling Weakly-Supervised Temporal Action Localization from On-Device Learning of the Video Stream—0
Curvature: A signature for Action Recognition in Video Sequences—0
A Review on Coarse to Fine-Grained Animal Action Recognition—0
Action Spotting and Precise Event Detection in Sports: Datasets, Methods, and Challenges—0
Cross-View Action Recognition via a Continuous Virtual Path—0
Cross-view Action Modeling, Learning and Recognition—0
Enhanced skeleton visualization for view invariant human action recognition—0
Enhanced Spatiotemporal Prediction Using Physical-guided And Frequency-enhanced Recurrent Neural Networks—0
A real-time algorithm for human action recognition in RGB and thermal video—0
Cross-Video Contextual Knowledge Exploration and Exploitation for Ambiguity Reduction in Weakly Supervised Temporal Action Localization—0
Boosting Point-Supervised Temporal Action Localization through Integrating Query Reformation and Optimal Transport—0
Ensemble One-dimensional Convolution Neural Networks for Skeleton-based Action Recognition—0
Ensembles of Deep Neural Networks for Action Recognition in Still Images—0
Cross-Stage Transformer for Video Learning—0
Actions in the Eye: Dynamic Gaze Datasets and Learnt Saliency Models for Visual Recognition—0
Application-Driven AI Paradigm for Human Action Recognition—0
Cross-Modal Message Passing for Two-stream Fusion—0
Evaluating the Effectiveness of Automated Identity Masking (AIM) Methods with Human Perception and a Deep Convolutional Neural Network (CNN)—0
Evaluating Transformers for Lightweight Action Recognition—0
Evaluation of Color STIPs for Human Action Recognition—0
Event-based Action Recognition Using Timestamp Image Encoding Network—0
Action Classification via Concepts and Attributes—0
Forcing the Whole Video as Background: An Adversarial Learning Strategy for Weakly Temporal Action Localization—0
Boundary Uncertainty in a Single-Stage Temporal Action Localization Network—0
Evolution-Preserving Dense Trajectory Descriptors—0
Bregman Divergences for Infinite Dimensional Covariance Matrices—0
EXMOVES: Classifier-based Features for Scalable 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
fpgaHART: A toolflow for throughput-oriented acceleration of 3D CNNs for HAR onto FPGAs—0
Exploiting Language Models for Visual Recognition—0
Exploiting Spatial-Temporal Modelling and Multi-Modal Fusion for Human Action Recognition—0
Exploiting Structure Sparsity for Covariance-based Visual Representation—0
From Synsets to Videos: Enriching ItalWordNet Multimodally—0
Exploring Denoised Cross-Video Contrast for Weakly-Supervised Temporal Action Localization—0
Action Sensitivity Learning for Temporal Action Localization—0
Exploring Feature Representation and Training strategies in Temporal Action Localization—0
Exploring Frame Segmentation Networks for Temporal Action Localization—0
Flip-Invariant Motion Representation—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