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
Exploring Stronger Feature for Temporal Action Localization—0
Exploring Sub-Pseudo Labels for Learning from Weakly-Labeled Web Videos—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
Hierarchical Feature Aggregation Networks for Video Action Recognition—0
Extended multi-stream temporal-attention module for skeleton-based human action recognition (HAR)—0
Extending Temporal Data Augmentation for Video Action Recognition—0
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds—0
Action Sensitivity Learning for Temporal Action Localization—0
F4D: Factorized 4D Convolutional Neural Network for Efficient Video-level Representation Learning—0
A Novel Online Action Detection Framework from Untrimmed Video Streams—0
Hand-Object Interaction and Precise Localization in Transitive Action Recognition—0
Harnessing Object and Scene Semantics for Large-Scale Video Understanding—0
Cross Domain Model Compression by Structurally Weight Sharing—0
A Novel Locally Linear KNN Model for Visual Recognition—0
Action Capsules: Human Skeleton Action Recognition—0
Cricket stroke extraction: Towards creation of a large-scale cricket actions dataset—0
Coupled Recurrent Network (CRN)—0
A Novel Geometric Framework on Gram Matrix Trajectories for Human Behavior Understanding—0
Handcrafted localized phase features for human action recognition—0
Harnessing the Deep Net Object Models for Enhancing Human Action Recognition—0
A Novel Approach for Robust Multi Human Action Recognition and Summarization based on 3D Convolutional Neural Networks—0
Could Giant Pretrained Image Models Extract Universal Representations?—0
Action Representation Using Classifier Decision Boundaries—0
Correlation Net: Spatiotemporal multimodal deep learning for action recognition—0
Cooperative Training of Deep Aggregation Networks for RGB-D Action Recognition—0
A Novel Approach for Human Action Recognition from Silhouette Images—0
A^2-Nets: Double Attention Networks—0
Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization—0
Cooperative Cross-Stream Network for Discriminative Action Representation—0
A Nonparametric Bayesian Approach Toward Stacked Convolutional Independent Component Analysis—0
Cooking in the kitchen: Recognizing and Segmenting Human Activities in Videos—0
Co-Occurrence Matters: Learning Action Relation for Temporal Action Localization—0
Annotation Methodologies for Vision and Language Dataset Creation—0
Action-Attending Graphic Neural Network—0
Handcrafted Local Features are Convolutional Neural Networks—0
Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition—0
Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks—0
Annotation-Efficient Untrimmed Video Action Recognition—0
Action Recognition with Spatio-Temporal Visual Attention on Skeleton Image Sequences—0
An Information-rich Sampling Technique over Spatio-Temporal CNN for Classification of Human Actions in Videos—0
Group sparsity and geometry constrained dictionary learning for action recognition from depth maps.—0
Convolutional Architecture Exploration for Action Recognition and Image Classification—0
An Improved Video Analysis using Context based Extension of LSH—0
Action Recognition with Joint Attention on Multi-Level Deep Features—0
Contrastive Language-Action Pre-training for Temporal Localization—0
A New Representation of Skeleton Sequences for 3D Action Recognition—0
3D R Transform on Spatio-temporal Interest Points for Action Recognition—0
GTA: Global Temporal Attention for Video Action Understanding—0
Continuous Video to Simple Signals for Swimming Stroke Detection with Convolutional Neural Networks—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