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Temporal Action Localization

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하위 태스크: 8
평가표: 14
보존된 평가 기록: 125

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.

코드

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

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

공식 코드

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

https://github.com/au-revoir/model-editing-ft

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Model Editing by Standard Fine-Tuning

https://github.com/axd465/PAM_Deep_Learning_Undersampling_Publication

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Reconstructing undersampled photoacoustic microscopy images using deep learning

https://github.com/azzam-alhussain/fpga-qhar

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FPGA-QHAR: Throughput-Optimized for Quantized Human Action Recognition on The Edge

https://github.com/azzh1/purls

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Part-aware Unified Representation of Language and Skeleton for Zero-shot Action Recognition

https://github.com/baaivision/eva

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EVA: Exploring the Limits of Masked Visual Representation Learning at Scale

https://github.com/bahjat-kawar/time-diffusion

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Editing Implicit Assumptions in Text-to-Image Diffusion Models

https://github.com/baixianghuang/behavior-edit

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Model Editing as a Double-Edged Sword: Steering Agent Ethical Behavior Toward Beneficence or Harm

https://github.com/bboylyg/expose-before-you-defend

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Expose Before You Defend: Unifying and Enhancing Backdoor Defenses via Exposed Models

https://github.com/bebr2/editcot

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Knowledge Editing through Chain-of-Thought

https://github.com/beepkh/unike

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Towards Unified Multimodal Editing with Enhanced Knowledge Collaboration

https://github.com/benedettaliberatori/t3al

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Test-Time Zero-Shot Temporal Action Localization

https://github.com/bfshi/DGAM-Weakly-Supervised-Action-Localization

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Weakly-Supervised Action Localization by Generative Attention Modeling

https://github.com/bghojogh/Fisherposes

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Recognizing Involuntary Actions from 3D Skeleton Data Using Body States

https://github.com/bghojogh/Roweisposes

공식 코드

Roweisposes, Including Eigenposes, Supervised Eigenposes, and Fisherposes, for 3D Action Recognition

https://github.com/bigai-ai/ICE

공식 코드

In-Context Editing: Learning Knowledge from Self-Induced Distributions

https://github.com/bmartacho/UniPose

공식 코드

UniPose: Unified Human Pose Estimation in Single Images and Videos

https://github.com/boheumd/asm-loc

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ASM-Loc: Action-aware Segment Modeling for Weakly-Supervised Temporal Action Localization

https://github.com/boneddeng/tadml

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TadML: A fast temporal action detection with Mechanics-MLP

https://github.com/bouracha/OoDMotion

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Generative Model-Enhanced Human Motion Prediction

https://github.com/bradleywang0416/gcnext

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GCNext: Towards the Unity of Graph Convolutions for Human Motion Prediction

https://github.com/brian7685/Multimodal-Clustering-Network

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Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos

https://github.com/brinkl/graphhetnet

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Few-shot human motion prediction for heterogeneous sensors

https://github.com/brjathu/LART

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On the Benefits of 3D Pose and Tracking for Human Action Recognition

https://github.com/bruthyu/melo

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MELO: Enhancing Model Editing with Neuron-Indexed Dynamic LoRA

https://github.com/bryanyzhu/Hidden-Two-Stream

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Hidden Two-Stream Convolutional Networks for Action Recognition

https://github.com/bshfang/self-supervised-motion

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Self-Supervised Bird's Eye View Motion Prediction with Cross-Modality Signals

https://github.com/btgraham/SparseConvNet

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Sparse 3D convolutional neural networks

https://github.com/buptsjzhang/std-cl

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Spatial-Temporal Decoupling Contrastive Learning for Skeleton-based Human Action Recognition

https://github.com/buptsjzhang/ta-mlp

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SiT-MLP: A Simple MLP with Point-wise Topology Feature Learning for Skeleton-based Action Recognition

https://github.com/buxiangzhiren/contextloc

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Enriching Local and Global Contexts for Temporal Action Localization

https://github.com/byronbbl/deck

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Decoding by Contrasting Knowledge: Enhancing LLMs' Confidence on Edited Facts

https://github.com/cagatayyildiz/ODE2VAE

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ODE$^2$VAE: Deep generative second order ODEs with Bayesian neural networks

https://github.com/camma-public/tripnet

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Recognition of Instrument-Tissue Interactions in Endoscopic Videos via Action Triplets

https://github.com/canbaoburen/CoDT

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Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action Recognition

https://github.com/cap-ntu/ML-Model-CI

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ModelPS: An Interactive and Collaborative Platform for Editing Pre-trained Models at Scale

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