SOTAVerified

Action Segmentation

Action Segmentation is a challenging problem in high-level video understanding. In its simplest form, Action Segmentation aims to segment a temporally untrimmed video by time and label each segmented part with one of pre-defined action labels. The results of Action Segmentation can be further used as input to various applications, such as video-to-text and action localization.

Source: TricorNet: A Hybrid Temporal Convolutional and Recurrent Network for Video Action Segmentation

Papers

Showing 110 of 219 papers

TitleStatusHype
Self-supervised pretraining of vision transformers for animal behavioral analysis and neural encoding0
HopaDIFF: Holistic-Partial Aware Fourier Conditioned Diffusion for Referring Human Action Segmentation in Multi-Person ScenariosCode0
EPFL-Smart-Kitchen-30: Densely annotated cooking dataset with 3D kinematics to challenge video and language modelsCode1
M2R2: MulitModal Robotic Representation for Temporal Action Segmentation0
Uni4D: A Unified Self-Supervised Learning Framework for Point Cloud Videos0
Towards Generalizing Temporal Action Segmentation to Unseen Views0
What Changed and What Could Have Changed? State-Change Counterfactuals for Procedure-Aware Video Representation Learning0
Cost-Sensitive Learning for Long-Tailed Temporal Action SegmentationCode0
Condensing Action Segmentation Datasets via Generative Network Inversion0
End-to-End Action Segmentation Transformer0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Semantic2GraphF1@50%91.3Unverified
2FACTF1@50%87.5Unverified
3DiffActF1@50%84.7Unverified
4BaFormerF1@50%83.5Unverified
5SF-TMN(ASFormer)F1@50%83.1Unverified
6Br-Prompt+ASFormerF1@50%83Unverified
7DPRNF1@50%82.9Unverified
8BITF1@50%82.6Unverified
9CETNetF1@50%81.3Unverified
10UVASTF1@50%81Unverified