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 951–1000 of 1477 papers

TitleStatusHype
When Kernel Methods meet Feature Learning: Log-Covariance Network for Action Recognition from Skeletal Data—0
When Spatial meets Temporal in Action Recognition—0
Where and when to look? Spatial-temporal attention for action recognition in videos—0
YH Technologies at ActivityNet Challenge 2018—0
You Lead, We Exceed: Labor-Free Video Concept Learning by Jointly Exploiting Web Videos and Images—0
Zero-Shot Action Recognition in Videos: A Survey—0
Zero-Shot Action Recognition With Error-Correcting Output Codes—0
Interpretable Spatio-temporal Attention for Video Action Recognition—0
In the Eye of Beholder: Joint Learning of Gaze and Actions in First Person Video—0
Investigation on Combining 3D Convolution of Image Data and Optical Flow to Generate Temporal Action Proposals—0
Invisible-to-Visible: Privacy-Aware Human Instance Segmentation using Airborne Ultrasound via Collaborative Learning Variational Autoencoder—0
JCDNet: Joint of Common and Definite phases Network for Weakly Supervised Temporal Action Localization—0
JEDI: Joint Expert Distillation in a Semi-Supervised Multi-Dataset Student-Teacher Scenario for Video Action Recognition—0
Joint Action Recognition and Pose Estimation From Video—0
Joint-bone Fusion Graph Convolutional Network for Semi-supervised Skeleton Action Recognition—0
Joint Denoising / Compression of Image Contours via Shape Prior and Context Tree—0
Joint Discriminative Bayesian Dictionary and Classifier Learning—0
Joint Learning On The Hierarchy Representation for Fine-Grained Human Action Recognition—0
Joint Max Margin and Semantic Features for Continuous Event Detection in Complex Scenes—0
Joint Network based Attention for Action Recognition—0
Joint Recognition and Segmentation of Actions via Probabilistic Integration of Spatio-Temporal Fisher Vectors—0
Joint Temporal Pooling for Improving Skeleton-based Action Recognition—0
JOLO-GCN: Mining Joint-Centered Light-Weight Information for Skeleton-Based Action Recognition—0
JUMPS: Joints Upsampling Method for Pose Sequences—0
Just Add ?! Pose Induced Video Transformers for Understanding Activities of Daily Living—0
KAN-HyperpointNet for Point Cloud Sequence-Based 3D Human Action Recognition—0
Kernelized Covariance for Action Recognition—0
Kinematic-Layout-aware Random Forests for Depth-based Action Recognition—0
Knowledge Fusion Transformers for Video Action Recognition—0
Knowledge Integration Networks for Action Recognition—0
KPCA Spatio-temporal trajectory point cloud classifier for recognizing human actions in a CBVR system—0
Label Efficient Learning of Transferable Representations acrosss Domains and Tasks—0
Label Efficient Learning of Transferable Representations across Domains and Tasks—0
LS-HAR: Language Supervised Human Action Recognition with Salient Fusion, Construction Sites as a Use-Case—0
Lattice Long Short-Term Memory for Human Action Recognition—0
LAVA: Language Audio Vision Alignment for Contrastive Video Pre-Training—0
Learn2Augment: Learning to Composite Videos for Data Augmentation in Action Recognition—0
Learning Actionness via Long-range Temporal Order Verification—0
Learning Action Recognition Model From Depth and Skeleton Videos—0
Learning a Deep Model for Human Action Recognition from Novel Viewpoints—0
Learning a discriminative hidden part model for human action recognition—0
Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks—0
Learning and Refining of Privileged Information-based RNNs for Action Recognition from Depth Sequences—0
Learning and Using the Arrow of Time—0
Learning a Non-Linear Knowledge Transfer Model for Cross-View Action Recognition—0
Learning a Pose Lexicon for Semantic Action Recognition—0
Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition—0
Learning Conditional Random Fields with Augmented Observations for Partially Observed Action Recognition—0
Learning Discriminative Motion Features Through Detection—0
Learning discriminative trajectorylet detector sets for accurate 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