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Action Segmentation

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하위 태스크: 4
평가표: 9
보존된 평가 기록: 120

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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/sahasuman/bmvc2016_code

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Online Spatiotemporal Action Detection and Prediction via Causal Representations

https://github.com/BehnooshParsa/HumanActionRecognition_with_ErgonomicRisk

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Toward Ergonomic Risk Prediction via Segmentation of Indoor Object Manipulation Actions Using Spatiotemporal Convolutional Networks

https://github.com/BorealisAI/TSC-Disc-Proto

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Learning Discriminative Prototypes with Dynamic Time Warping

https://github.com/CVPRUSFTampa/EventSegmentation

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A Perceptual Prediction Framework for Self Supervised Event Segmentation

https://github.com/MohsenFayyaz89/SCT

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SCT: Set Constrained Temporal Transformer for Set Supervised Action Segmentation

https://github.com/PaddlePaddle/PaddleVideo/blob/develop/docs/en/model_zoo/multimodal/actbert.md

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ActBERT: Learning Global-Local Video-Text Representations

https://github.com/QingZhong1996/OnlineTAS

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OnlineTAS: An Online Baseline for Temporal Action Segmentation

https://github.com/ShangHua-Gao/G2L-search

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Global2Local: Efficient Structure Search for Video Action Segmentation

https://github.com/ShangHua-Gao/RFNext

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RF-Next: Efficient Receptive Field Search for Convolutional Neural Networks

https://github.com/Thinksky5124/SVTAS

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Streaming Video Temporal Action Segmentation In Real Time

https://github.com/Wangjhdeveloper/CETNet

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Cross-Enhancement Transformer for Action Segmentation

https://github.com/ZheLi2020/TimestampActionSeg

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Temporal Action Segmentation from Timestamp Supervision

https://github.com/ablau100/daart

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A study of animal action segmentation algorithms across supervised, unsupervised, and semi-supervised learning paradigms

https://github.com/adamgoldbraikh/ms-tcrnet

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MS-TCRNet: Multi-Stage Temporal Convolutional Recurrent Networks for Action Segmentation Using Sensor-Augmented Kinematics

https://github.com/aiotgroup/uwash

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You Can Wash Hands Better: Accurate Daily Handwashing Assessment with a Smartwatch

https://github.com/alexanderrichard/squirrel

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Weakly Supervised Action Learning with RNN based Fine-to-coarse Modeling

https://github.com/amathislab/epfl-smart-kitchen

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EPFL-Smart-Kitchen-30: Densely annotated cooking dataset with 3D kinematics to challenge video and language models

https://github.com/annusha/unsup_temp_embed

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Unsupervised learning of action classes with continuous temporal embedding

https://github.com/antoine77340/MIL-NCE_HowTo100M

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End-to-End Learning of Visual Representations from Uncurated Instructional Videos

https://github.com/assembly101/assembly101.github.io

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Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural Activities

https://github.com/atlas-eccv22/awesome-temporal-action-segmentation

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Temporal Action Segmentation: An Analysis of Modern Techniques

https://github.com/benjaminfiltjens/ms-gcn

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Automated freezing of gait assessment with marker-based motion capture and multi-stage spatial-temporal graph convolutional neural networks

https://github.com/boschresearch/uvast

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Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation

https://github.com/chinayi/asformer

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ASFormer: Transformer for Action Segmentation

https://github.com/cmhungsteve/SSTDA

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Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation

https://github.com/ddz16/TSASPC

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Timestamp-Supervised Action Segmentation from the Perspective of Clustering

https://github.com/ddz16/TUT

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Do we really need temporal convolutions in action segmentation?

https://github.com/dipika-singhania/C2F-TCN

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Coarse to Fine Multi-Resolution Temporal Convolutional Network

https://github.com/dipika-singhania/ICC-Semi-Supervised-TAS

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Iterative Contrast-Classify For Semi-supervised Temporal Action Segmentation

https://github.com/dpfried/action-segmentation

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Learning to Segment Actions from Observation and Narration

https://github.com/elenabbbuenob/tsa-actionseg

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Leveraging triplet loss for unsupervised action segmentation

https://github.com/facebookresearch/vlamp

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Pretrained Language Models as Visual Planners for Human Assistance

https://github.com/fedespu/hvq

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Hierarchical Vector Quantization for Unsupervised Action Segmentation

https://github.com/feixiangzhou/smc-nca

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SMC-NCA: Semantic-guided Multi-level Contrast for Semi-supervised Temporal Action Segmentation

https://github.com/geekfeiw/WiSLAR

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Temporal Unet: Sample Level Human Action Recognition using WiFi

https://github.com/gongda0e/kari

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Activity Grammars for Temporal Action Segmentation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.