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 751–800 of 1477 papers

TitleStatusHype
Multi-Modal Three-Stream Network for Action Recognition—0
Graph Convolutional Networks for Temporal Action LocalizationCode0
Mobile Video Action Recognition—0
Cooperative Cross-Stream Network for Discriminative Action Representation—0
3C-Net: Category Count and Center Loss for Weakly-Supervised Action LocalizationCode0
Human activity recognition from skeleton posesCode0
Three Branches: Detecting Actions With Richer Features—0
I3D-LSTM: A New Model for Human Action RecognitionCode0
Adversarial Seeded Sequence Growing for Weakly-Supervised Temporal Action Localization—0
STM: SpatioTemporal and Motion Encoding for Action Recognition—0
Action Recognition in Untrimmed Videos with Composite Self-Attention Two-Stream Framework—0
Scale Matters: Temporal Scale Aggregation Network for Precise Action Localization in Untrimmed Videos—0
SkeleMotion: A New Representation of Skeleton Joint Sequences Based on Motion Information for 3D Action RecognitionCode0
Multi-Granularity Fusion Network for Proposal and Activity Localization: Submission to ActivityNet Challenge 2019 Task 1 and Task 2—0
A Novel Approach for Robust Multi Human Action Recognition and Summarization based on 3D Convolutional Neural Networks—0
Submission to ActivityNet Challenge 2019: Task B Spatio-temporal Action Localization—0
TARN: Temporal Attentive Relation Network for Few-Shot and Zero-Shot Action Recognition—0
Spatiotemporal graph routing for skeleton-based action recognition—0
Slow Feature Analysis for Human Action Recognition—0
Two-stream Spatiotemporal Feature for Video QA Task—0
Video Action Recognition Via Neural Architecture Searching—0
A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data—0
A Comparative Review of Recent Kinect-based Action Recognition AlgorithmsCode0
Understanding More about Human and Machine Attention in Deep Neural Networks—0
R-STAN: Residual Spatial-Temporal Attention Network for Action Recognition—0
Trimmed Action Recognition, Dense-Captioning Events in Videos, and Spatio-temporal Action Localization with Focus on ActivityNet Challenge 2019—0
Learning Spatio-Temporal Representation with Local and Global DiffusionCode0
Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video dataCode0
PA3D: Pose-Action 3D Machine for Video Recognition—0
Bayesian Hierarchical Dynamic Model for Human Action RecognitionCode0
Progressive Teacher-Student Learning for Early Action Prediction—0
Self-Supervised Spatiotemporal Learning via Video Clip Order Prediction—0
Collaborative Spatiotemporal Feature Learning for Video Action RecognitionCode0
Completeness Modeling and Context Separation for Weakly Supervised Temporal Action LocalizationCode0
Skeleton-Based Action Recognition With Directed Graph Neural NetworksCode0
Cross Domain Model Compression by Structurally Weight Sharing—0
MARS: Motion-Augmented RGB Stream for Action RecognitionCode0
MFAS: Multimodal Fusion Architecture SearchCode0
Action4D: Online Action Recognition in the Crowd and Clutter—0
Rethinking Full Connectivity in Recurrent Neural Networks—0
What Makes Training Multi-Modal Classification Networks Hard?Code0
Hierarchical Feature Aggregation Networks for Video Action Recognition—0
Improving Action Localization by Progressive Cross-stream Cooperation—0
Exploring Feature Representation and Training strategies in Temporal Action Localization—0
Marginalized Average Attentional Network for Weakly-Supervised Learning—0
Representation Learning on Visual-Symbolic Graphs for Video Understanding—0
Richly Activated Graph Convolutional Network for Action Recognition with Incomplete SkeletonsCode0
Towards a Skeleton-Based Action Recognition For Realistic Scenarios—0
Spatio-Temporal Action Localization in a Weakly Supervised Setting—0
Large-scale weakly-supervised pre-training for video action recognitionCode0
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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