https://github.com/bigai-ai/ICE
공식 코드In-Context Editing: Learning Knowledge from Self-Induced Distributions
Papers with Code 아카이브
Action Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 15
- 평가표
- 56
- 보존된 평가 기록
- 650
Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.
In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.
Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/bmartacho/UniPose
공식 코드UniPose: Unified Human Pose Estimation in Single Images and Videos
https://github.com/bochenxie/neurohar
공식 코드Event Voxel Set Transformer for Spatiotemporal Representation Learning on Event Streams
https://github.com/bomri/SlowFast/blob/master/projects/vtn/README.md
공식 코드https://github.com/brjathu/LART
공식 코드On the Benefits of 3D Pose and Tracking for Human Action Recognition
https://github.com/brown-palm/AntGPT
공식 코드AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?
https://github.com/brown-palm/ObjectPrompt
공식 코드Object-centric Video Representation for Long-term Action Anticipation
https://github.com/bruceyo/V-PETL
공식 코드Towards a Unified View on Visual Parameter-Efficient Transfer Learning
https://github.com/bruthyu/melo
공식 코드MELO: Enhancing Model Editing with Neuron-Indexed Dynamic LoRA
https://github.com/bryant1410/fitclip
공식 코드FitCLIP: Refining Large-Scale Pretrained Image-Text Models for Zero-Shot Video Understanding Tasks
https://github.com/bryant1410/tclip
공식 코드FitCLIP: Refining Large-Scale Pretrained Image-Text Models for Zero-Shot Video Understanding Tasks
https://github.com/bryanyzhu/Hidden-Two-Stream
공식 코드Hidden Two-Stream Convolutional Networks for Action Recognition
https://github.com/buptsjzhang/std-cl
공식 코드Spatial-Temporal Decoupling Contrastive Learning for Skeleton-based Human Action Recognition
https://github.com/buptsjzhang/ta-mlp
공식 코드https://github.com/byronbbl/deck
공식 코드Decoding by Contrasting Knowledge: Enhancing LLMs' Confidence on Edited Facts
https://github.com/camma-public/attention-tripnet
공식 코드https://github.com/camma-public/cholectriplet2022
공식 코드https://github.com/camma-public/ivtmetrics
공식 코드Data Splits and Metrics for Method Benchmarking on Surgical Action Triplet Datasets
https://github.com/camma-public/rendezvous-in-time
공식 코드Rendezvous in Time: An Attention-based Temporal Fusion approach for Surgical Triplet Recognition
https://github.com/camma-public/selfsupsurg
공식 코드Dissecting Self-Supervised Learning Methods for Surgical Computer Vision
https://github.com/camma-public/surglatentgraph
공식 코드Encoding Surgical Videos as Latent Spatiotemporal Graphs for Object and Anatomy-Driven Reasoning
https://github.com/camma-public/tripnet
공식 코드Recognition of Instrument-Tissue Interactions in Endoscopic Videos via Action Triplets
https://github.com/canbaoburen/CoDT
공식 코드https://github.com/cap-ntu/ML-Model-CI
공식 코드ModelPS: An Interactive and Collaborative Platform for Editing Pre-trained Models at Scale
https://github.com/carlobretti/object-scene-compositions-for-actions
공식 코드Zero-Shot Action Recognition from Diverse Object-Scene Compositions
https://github.com/carloscaetano/skeleton-images
공식 코드https://github.com/caskcsg/lyaplock
공식 코드LyapLock: Bounded Knowledge Preservation in Sequential Large Language Model Editing
https://github.com/changchangsun/forget-vector
공식 코드https://github.com/chaoyuaw/lvu
공식 코드https://github.com/chenhaoxing/etl4video
공식 코드Efficient Transfer Learning for Video-language Foundation Models
https://github.com/chenhsing/svformer
공식 코드SVFormer: Semi-supervised Video Transformer for Action Recognition
https://github.com/chenhuihu/knowledge_in_superposition
공식 코드https://github.com/chenhuihu/wilke
공식 코드WilKE: Wise-Layer Knowledge Editor for Lifelong Knowledge Editing
https://github.com/chenmientan/malmen
공식 코드https://github.com/chenyirui/gim
공식 코드GIM: A Million-scale Benchmark for Generative Image Manipulation Detection and Localization
https://github.com/chihyaoma/Activity-Recognition-with-CNN-and-RNN
공식 코드TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity Recognition
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.