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 1101–1150 of 1477 papers

TitleStatusHype
Action recognition by learning pose representations—0
Enhanced skeleton visualization for view invariant human action recognition—0
Learning from Video and Text via Large-Scale Discriminative ClusteringCode0
Automatic Curation of Golf Highlights using Multimodal Excitement Features—0
Spatio-temporal Human Action Localisation and Instance Segmentation in Temporally Untrimmed Videos—0
Multi-kernel learning of deep convolutional features for action recognition—0
Temporal Convolution Based Action Proposal: Submission to ActivityNet 2017—0
Discriminative convolutional Fisher vector network for action recognition—0
Skeleton-Based Human Action Recognition with Global Context-Aware Attention LSTM Networks—0
Developing the Path Signature Methodology and its Application to Landmark-based Human Action Recognition—0
Skeleton-based Action Recognition Using LSTM and CNN—0
Learning Human Pose Models from Synthesized Data for Robust RGB-D Action Recognition—0
Spatio-Temporal Vector of Locally Max Pooled Features for Action Recognition in Videos—0
Spatio-Temporal Naive-Bayes Nearest-Neighbor (ST-NBNN) for Skeleton-Based Action RecognitionCode0
Multi-Task Clustering of Human Actions by Sharing Information—0
Modeling Sub-Event Dynamics in First-Person Action Recognition—0
Global Context-Aware Attention LSTM Networks for 3D Action Recognition—0
Joint Discriminative Bayesian Dictionary and Classifier Learning—0
Temporal Residual Networks for Dynamic Scene RecognitionCode0
Deep Sequential Context Networks for Action Prediction—0
Binary Coding for Partial Action Analysis With Limited Observation Ratios—0
Zero-Shot Action Recognition With Error-Correcting Output Codes—0
Alternative Semantic Representations for Zero-Shot Human Action Recognition—0
Recurrent Residual Learning for Action Recognition—0
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates—0
Detekcja upadku i wybranych akcji na sekwencjach obrazów cyfrowych—0
Learning without Prejudice: Avoiding Bias in Webly-Supervised Action Recognition—0
Action Search: Spotting Actions in Videos and Its Application to Temporal Action LocalizationCode0
Joint Max Margin and Semantic Features for Continuous Event Detection in Complex Scenes—0
Learning to Learn from Noisy Web Videos—0
Concurrence-Aware Long Short-Term Sub-Memories for Person-Person Action Recognition—0
Deep manifold-to-manifold transforming network for action recognition—0
Continuous Video to Simple Signals for Swimming Stroke Detection with Convolutional Neural Networks—0
Sequence Summarization Using Order-constrained Kernelized Feature Subspaces—0
Two-Stream 3D Convolutional Neural Network for Skeleton-Based Action Recognition—0
Ridiculously Fast Shot Boundary Detection with Fully Convolutional Neural NetworksCode0
Learning Spatiotemporal Features for Infrared Action Recognition with 3D Convolutional Neural Networks—0
Single Image Action Recognition by Predicting Space-Time Saliency—0
An Improved Video Analysis using Context based Extension of LSH—0
Deep Spatio-temporal Manifold Network for Action Recognition—0
CHAM: action recognition using convolutional hierarchical attention model—0
Action Tubelet Detector for Spatio-Temporal Action LocalizationCode0
Investigation of Different Skeleton Features for CNN-based 3D Action RecognitionCode0
Joint Denoising / Compression of Image Contours via Shape Prior and Context Tree—0
Action Understanding with Multiple Classes of Actors—0
An Analysis of Action Recognition Datasets for Language and Vision Tasks—0
Body Joint guided 3D Deep Convolutional Descriptors for Action Recognition—0
Second-order Temporal Pooling for Action Recognition—0
Context-based Object Viewpoint Estimation: A 2D Relational Approach—0
Skeleton Boxes: Solving skeleton based action detection with a single deep convolutional neural network—0
Show:102550
← PrevPage 23 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