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 651–700 of 1477 papers

TitleStatusHype
Knowledge Fusion Transformers for Video Action Recognition—0
Event-based Action Recognition Using Timestamp Image Encoding Network—0
PERF-Net: Pose Empowered RGB-Flow Net—0
Collaborative Distillation in the Parameter and Spectrum Domains for Video Action Recognition—0
View-invariant action recognition—0
Boundary Uncertainty in a Single-Stage Temporal Action Localization Network—0
Two-Stream Networks for Lane-Change Prediction of Surrounding Vehicles—0
Temporal Action Localization with Variance-Aware Networks—0
Towards Improved Human Action Recognition Using Convolutional Neural Networks and Multimodal Fusion of Depth and Inertial Sensor Data—0
Multidomain Multimodal Fusion For Human Action Recognition Using Inertial Sensors—0
Accuracy and Performance Comparison of Video Action Recognition Approaches—0
CFAD: Coarse-to-Fine Action Detector for Spatiotemporal Action Localization—0
Equivalent Classification Mapping for Weakly Supervised Temporal Action Localization—0
ConvGRU in Fine-grained Pitching Action Recognition for Action Outcome PredictionCode0
Richly Activated Graph Convolutional Network for Robust Skeleton-based Action RecognitionCode0
Single-stage intake gesture detection using CTC loss and extended prefix beam searchCode0
Boundary Content Graph Neural Network for Temporal Action Proposal Generation—0
Residual Frames with Efficient Pseudo-3D CNN for Human Action Recognition—0
Vision and Inertial Sensing Fusion for Human Action Recognition : A Review—0
Learning Actionness via Long-range Temporal Order Verification—0
Shuffle and Attend: Video Domain Adaptation—0
Mix Dimension in Poincaré Geometry for 3D Skeleton-based Action Recognition—0
Perceptron Synthesis Network: Rethinking the Action Scale Variances in Videos—0
Depthwise Spatio-Temporal STFT Convolutional Neural Networks for Human Action Recognition—0
Hierarchical Contrastive Motion Learning for Video Action Recognition—0
Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020—0
Multitask Non-Autoregressive Model for Human Motion Prediction—0
Representation Learning via Adversarially-Contrastive Optimal Transport—0
Learning Speech Representations from Raw Audio by Joint Audiovisual Self-Supervision—0
Complex Human Action Recognition in Live Videos Using Hybrid FR-DL Method—0
Weakly Supervised Temporal Action Localization with Segment-Level Labels—0
JUMPS: Joints Upsampling Method for Pose Sequences—0
Path Signatures on Lie GroupsCode0
Roweisposes, Including Eigenposes, Supervised Eigenposes, and Fisherposes, for 3D Action RecognitionCode0
3DFCNN: Real-Time Action Recognition using 3D Deep Neural Networks with Raw Depth Information—0
Exploiting the ConvLSTM: Human Action Recognition using Raw Depth Video-Based Recurrent Neural Networks—0
DTG-Net: Differentiated Teachers Guided Self-Supervised Video Action Recognition—0
Temporal Fusion Network for Temporal Action Localization:Submission to ActivityNet Challenge 2020 (Task E)—0
Learning Temporal Co-Attention Models for Unsupervised Video Action LocalizationCode0
Regularization on Spatio-Temporally Smoothed Feature for Action Recognition—0
Context Aware Graph Convolution for Skeleton-Based Action Recognition—0
Action recognition in real-world videos—0
Combining Deep Learning Classifiers for 3D Action Recognition—0
Spatiotemporal Fusion in 3D CNNs: A Probabilistic View—0
What and Where: Modeling Skeletons from Semantic and Spatial Perspectives for Action Recognition—0
Human action recognition with a large-scale brain-inspired photonic computer—0
Ensembles of Deep Neural Networks for Action Recognition in Still Images—0
A Novel Online Action Detection Framework from Untrimmed Video Streams—0
Skeleton Based Action Recognition using a Stacked Denoising Autoencoder with Constraints of Privileged Information—0
Unifying Graph Embedding Features with Graph Convolutional Networks for Skeleton-based Action Recognition—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