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
Action4D: Real-time Action Recognition in the Crowd and Clutter—0
Squeeze-and-Excitation on Spatial and Temporal Deep Feature Space for Action Recognition—0
SSNet: Scale Selection Network for Online 3D Action Prediction—0
Making Convolutional Networks Recurrent for Visual Sequence Learning—0
Coding Kendall's Shape Trajectories for 3D Action Recognition—0
Recognize Actions by Disentangling Components of Dynamics—0
Pulling Actions out of Context: Explicit Separation for Effective Combination—0
Recognizing Human Actions as the Evolution of Pose Estimation Maps—0
Temporal Hallucinating for Action Recognition With Few Still Images—0
Learning and Using the Arrow of Time—0
Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition—0
PoseFlow: A Deep Motion Representation for Understanding Human Behaviors in Videos—0
Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning—0
PoTion: Pose MoTion Representation for Action Recognition—0
One-Shot Action Localization by Learning Sequence Matching Network—0
MiCT: Mixed 3D/2D Convolutional Tube for Human Action Recognition—0
RNN for Affects at SemEval-2018 Task 1: Formulating Affect Identification as a Binary Classification Problem—0
A Fine-to-Coarse Convolutional Neural Network for 3D Human Action Recognition—0
Pose-Based Two-Stream Relational Networks for Action Recognition in Videos—0
DEEPEYE: A Compact and Accurate Video Comprehension at Terminal Devices Compressed with Quantization and Tensorization—0
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning—0
Graph Edge Convolutional Neural Networks for Skeleton Based Action Recognition—0
Towards an Unequivocal Representation of Actions—0
Low-Latency Human Action Recognition with Weighted Multi-Region Convolutional Neural Network—0
Visual Attribute-augmented Three-dimensional Convolutional Neural Network for Enhanced Human Action Recognition—0
Skeleton-Based Action Recognition with Spatial Reasoning and Temporal Stack Learning—0
Relational Network for Skeleton-Based Action Recognition—0
Learning Optical Flow via Dilated Networks and Occlusion Reasoning—0
Object Activity Scene Description, Construction and Recognition—0
Actor and Observer: Joint Modeling of First and Third-Person VideosCode0
Memory Attention Networks for Skeleton-based Action RecognitionCode0
View Adaptive Neural Networks for High Performance Skeleton-based Human Action RecognitionCode0
Rethinking the Faster R-CNN Architecture for Temporal Action Localization—0
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
PM-GANs: Discriminative Representation Learning for Action Recognition Using Partial-modalities—0
Precise Temporal Action Localization by Evolving Temporal Proposals—0
STAIR Actions: A Video Dataset of Everyday Home ActionsCode0
Audio-Visual Scene Analysis with Self-Supervised Multisensory FeaturesCode0
DIY Human Action Data Set Generation—0
Non-Linear Temporal Subspace Representations for Activity Recognition—0
Video Representation Learning Using Discriminative Pooling—0
Adversarial Framework for Unsupervised Learning of Motion Dynamics in Videos—0
Towards Universal Representation for Unseen Action Recognition—0
T-RECS: Training for Rate-Invariant Embeddings by Controlling Speed for Action Recognition—0
Exploiting deep residual networks for human action recognition from skeletal data—0
Learning and Recognizing Human Action from Skeleton Movement with Deep Residual Neural Networks—0
Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition—0
Deja Vu: Motion Prediction in Static ImagesCode0
Featureless: Bypassing feature extraction in action categorization—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