https://bitbucket.org/bookcold/vandal_detection
공식 코드Wikipedia Vandal Early Detection: from User Behavior to User Embedding
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What is Human Pose Estimation? Human pose estimation is the process of estimating the configuration of the body (pose) from a single, typically monocular, image. Background. Human pose estimation is one of the key problems in computer vision that has been studied for well over 15 years. The reason for its importance is the abundance of applications that can benefit from such a technology. For example, human pose estimation allows for higher-level reasoning in the context of human-computer interaction and activity recognition; it is also one of the basic building blocks for marker-less motion capture (MoCap) technology. MoCap technology is useful for applications ranging from character animation to clinical analysis of gait pathologies.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Wikipedia Vandal Early Detection: from User Behavior to User Embedding
QuaSE: Accurate Text Style Transfer under Quantifiable Guidance
Challenges in Emotion Style Transfer: An Exploration with a Lexical Substitution Pipeline
CQASUMM: Building References for Community Question Answering Summarization Corpora
WikiAutoGen: Towards Multi-Modal Wikipedia-Style Article Generation
An Empirical Study on Prompt Compression for Large Language Models
ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification
Tackling Data Bias in Painting Classification with Style Transfer
Annotating and Detecting Fine-grained Factual Errors for Dialogue Summarization
Night-to-Day Image Translation for Retrieval-based Localization
Designing and Evaluating Presentation Strategies for Fact-Checked Content
Semantically Guided Representation Learning For Action Anticipation
GASP! Generating Abstracts of Scientific Papers from Abstracts of Cited Papers
SAFIN: Arbitrary Style Transfer With Self-Attentive Factorized Instance Normalization
StyleSinger: Style Transfer for Out-of-Domain Singing Voice Synthesis
TCSinger: Zero-Shot Singing Voice Synthesis with Style Transfer and Multi-Level Style Control
Two-Stream Action Recognition-Oriented Video Super-Resolution
Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model
A Divide-and-Conquer Approach to the Summarization of Long Documents
KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi
Listening between the Lines: Learning Personal Attributes from Conversations
IR-BERT: Leveraging BERT for Semantic Search in Background Linking for News Articles
AIO-P: Expanding Neural Performance Predictors Beyond Image Classification
Learning Truncated Causal History Model for Video Restoration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.