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 1051–1100 of 1477 papers

TitleStatusHype
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks—0
Label Efficient Learning of Transferable Representations across Domains and Tasks—0
Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action RecognitionCode0
Revisiting hand-crafted feature for action recognition: a set of improved dense trajectoriesCode0
Scalable and Compact 3D Action Recognition with Approximated RBF Kernel Machines—0
Highly Efficient Human Action Recognition with Quantum Genetic Algorithm Optimized Support Vector Machine—0
Predictive Learning: Using Future Representation Learning Variantial Autoencoder for Human Action Prediction—0
Appearance-and-Relation Networks for Video ClassificationCode0
Train, Diagnose and Fix: Interpretable Approach for Fine-grained Action Recognition—0
Multi-Level Recurrent Residual Networks for Action Recognition—0
Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion—0
Excitation Backprop for RNNsCode0
Action-Attending Graphic Neural Network—0
Skepxels: Spatio-temporal Image Representation of Human Skeleton Joints for Action Recognition—0
Attend and Interact: Higher-Order Object Interactions for Video Understanding—0
End-to-end Video-level Representation Learning for Action RecognitionCode0
Egocentric Hand Detection Via Dynamic Region Growing—0
Attentional Pooling for Action RecognitionCode0
3D CNNs on Distance Matrices for Human Action RecognitionCode0
Adaptive RNN Tree for Large-Scale Human Action Recognition—0
A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling—0
Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data—0
Learning to Recognize Actions from Limited Training Examples Using a Recurrent Spiking Neural Model—0
Real-Time Action Detection in Video Surveillance using Sub-Action Descriptor with Multi-CNNCode0
CAMREP- Concordia Action and Motion Repository—0
Ensemble Deep Learning for Skeleton-Based Action Recognition Using Temporal Sliding LSTM NetworksCode0
Flip-Invariant Motion Representation—0
Learning Action Recognition Model From Depth and Skeleton Videos—0
Summarization of User-Generated Sports Video by Using Deep Action Recognition Features—0
Human Action Forecasting by Learning Task Grammars—0
Viewpoint Invariant Action Recognition using RGB-D Videos—0
Multi-Label Zero-Shot Human Action Recognition via Joint Latent Ranking Embedding—0
Learning Gating ConvNet for Two-Stream based Methods in Action RecognitionCode0
Detecting Hands in Egocentric Videos: Towards Action Recognition—0
A Compact Kernel Approximation for 3D Action Recognition—0
Multi-label Class-imbalanced Action Recognition in Hockey Videos via 3D Convolutional Neural Networks—0
Natural Language Descriptions for Human Activities in Video Streams—0
Two-stream Flow-guided Convolutional Attention Networks for Action RecognitionCode0
Learning Spatio-Temporal Features with 3D Residual Networks for Action RecognitionCode0
Hierarchical Multi-scale Attention Networks for Action Recognition—0
Human Action Recognition System using Good Features and Multilayer Perceptron Network—0
Recognizing Involuntary Actions from 3D Skeleton Data Using Body StatesCode0
Attentive Semantic Video Generation using CaptionsCode0
Pillar Networks++: Distributed non-parametric deep and wide networks—0
Eigen Evolution Pooling for Human Action Recognition—0
Lattice Long Short-Term Memory for Human Action Recognition—0
Exploring Temporal Preservation Networks for Precise Temporal Action Localization—0
Unsupervised Representation Learning by Sorting SequencesCode0
Attention Transfer from Web Images for Video Recognition—0
When Kernel Methods meet Feature Learning: Log-Covariance Network for Action Recognition from Skeletal Data—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