https://github.com/kaai520/PGFA
공식 코드Zero-shot Skeleton-based Action Recognition with Prototype-guided Feature Alignment
Papers with Code 아카이브
Activity Recognition
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- 평가표
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- 보존된 평가 기록
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Human Activity Recognition is the problem of identifying events performed by humans given a video input. It is formulated as a binary (or multiclass) classification problem of outputting activity class labels. Activity Recognition is an important problem with many societal applications including smart surveillance, video search/retrieval, intelligent robots, and other monitoring systems.
Source: Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/kahnchana/mvu
공식 코드https://github.com/kahnchana/svt
공식 코드https://github.com/kailliang/Lane-Change-Classification-and-Prediction-with-Action-Recognition-Networks
공식 코드Lane Change Classification and Prediction with Action Recognition Networks
https://github.com/kaist-dmlab/monaq
공식 코드https://github.com/kaiyoo/precondition-and-effect-reasoning-for-action-recognition
공식 코드https://github.com/kakashiz/nedb-net
공식 코드Noise and Edge Based Dual Branch Image Manipulation Detection
https://github.com/kaleab-k/VideoAT
공식 코드Analysis and Extensions of Adversarial Training for Video Classification
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/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/aras-dataset
공식 코드Mitigating Representation Bias in Action Recognition: Algorithms and Benchmarks
https://github.com/kennymckormick/pyskl
공식 코드PYSKL: Towards Good Practices for Skeleton Action Recognition
https://github.com/kennymckormick/transrank
공식 코드https://github.com/kenshohara/3D-ResNets
공식 코드Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition
https://github.com/kenshohara/3D-ResNets-PyTorch
공식 코드Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
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/kevinz8866/epo
공식 코드EPO: Hierarchical LLM Agents with Environment Preference Optimization
https://github.com/keynekassapa13/LAC
공식 코드Self-Supervised Contrastive Learning for Videos using Differentiable Local Alignment
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/khu-vll/glad
공식 코드https://github.com/khuvll/glad
공식 코드https://github.com/kikihub/consense
공식 코드ConSense: Continually Sensing Human Activity with WiFi via Growing and Picking
https://github.com/kimihiroh/promqa
공식 코드ProMQA: Question Answering Dataset for Multimodal Procedural Activity Understanding
https://github.com/kini5gowda/TruZe
공식 코드A New Split for Evaluating True Zero-Shot Action Recognition
https://github.com/kini5gowda/stories
공식 코드Telling Stories for Common Sense Zero-Shot Action Recognition
https://github.com/kiyoon/channel_sampling
공식 코드Capturing Temporal Information in a Single Frame: Channel Sampling Strategies for Action Recognition
https://github.com/kiyoon/verb_ambiguity
공식 코드An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition
https://github.com/kiyoon/video-adversarial-augmentation
공식 코드https://github.com/kkahatapitiya/SSDet
공식 코드Weakly-guided Self-supervised Pretraining for Temporal Activity Detection
https://github.com/klauscc/tallformer
공식 코드TALLFormer: Temporal Action Localization with a Long-memory Transformer
https://github.com/kmeng01/rome
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.