Papers with Code 아카이브
Temporal Action Localization
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- 하위 태스크
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- 평가표
- 14
- 보존된 평가 기록
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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/kakaobrain/flame
공식 코드https://github.com/kakashiz/nedb-net
공식 코드Noise and Edge Based Dual Branch Image Manipulation Detection
https://github.com/kalpitthakkar/pb-gcn
공식 코드Part-based Graph Convolutional Network for Action Recognition
https://github.com/kathpra/lshr_lsht
공식 코드Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition
https://github.com/kawakera-lab/crossmodeltransfer
공식 코드Cross-Model Transfer of Task Vectors via Few-Shot Orthogonal Alignment
https://github.com/kay1794/mmvp-motion-matrix-based-video-prediction
공식 코드https://github.com/kebii/r2et
공식 코드Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry
https://github.com/keltin13/concept-rot
공식 코드Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing
https://github.com/kennymckormick/pyskl
공식 코드PYSKL: Towards Good Practices for Skeleton Action Recognition
https://github.com/kenshohara/3D-ResNets
공식 코드Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition
https://github.com/kenziyuliu/ms-g3d
공식 코드Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition
https://github.com/kevin-ssy/Optical-Flow-Guided-Feature
공식 코드Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition
https://github.com/khadidja-delloul/rgb-d-theatre-scenes-dataset
공식 코드TS-RGBD Dataset: a Novel Dataset for Theatre Scenes Description for People with Visual Impairments
https://github.com/khu-vll/devias
공식 코드DEVIAS: Learning Disentangled Video Representations of Action and Scene
https://github.com/kit-mrt/future-motion
공식 코드https://github.com/kit-mrt/red-motion
공식 코드https://github.com/kit-mrt/road-barlow-twins
공식 코드https://github.com/kiyoon/video-adversarial-augmentation
공식 코드https://github.com/kkanshul/Hide-and-Seek
공식 코드Hide-and-Seek: A Data Augmentation Technique for Weakly-Supervised Localization and Beyond
https://github.com/klauscc/tallformer
공식 코드TALLFormer: Temporal Action Localization with a Long-memory Transformer
https://github.com/kmeng01/rome
공식 코드https://github.com/kowoonho/arfree
공식 코드Autoregression-free video prediction using diffusion model for mitigating error propagation
https://github.com/koyumizutani/earthquake
공식 코드https://github.com/kpeng9510/os-sar
공식 코드Navigating Open Set Scenarios for Skeleton-based Action Recognition
https://github.com/kpeng9510/proformer
공식 코드Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse Occlusions
https://github.com/kpeng9510/ravar
공식 코드https://github.com/kpeng9510/trans4soar
공식 코드Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse Occlusions
https://github.com/kracwarlock/action-recognition-visual-attention
공식 코드https://github.com/krystalan/bi_zsre
공식 코드https://github.com/kth-rpl/detect_vlm
공식 코드Hard Cases Detection in Motion Prediction by Vision-Language Foundation Models
https://github.com/kth-rpl/rmp
공식 코드https://github.com/kwwcv/selfmotion
공식 코드https://github.com/kwwcv/ssmp
공식 코드Semi-Supervised Class-Agnostic Motion Prediction with Pseudo Label Regeneration and BEVMix
https://github.com/kylemin/A2CL-PT
공식 코드Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization
https://github.com/l1bra1/rigidflow
공식 코드Self-Supervised 3D Scene Flow Estimation and Motion Prediction using Local Rigidity Prior
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.