https://github.com/marija-stanojevic/crime-analysis-2020
공식 코드Extracting Entities and Topics from News and Connecting Criminal Records
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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.
Extracting Entities and Topics from News and Connecting Criminal Records
Introducing Intermediate Domains for Effective Self-Training during Test-Time
In Plain Sight: Media Bias Through the Lens of Factual Reporting
Reformulating Unsupervised Style Transfer as Paraphrase Generation
Machine learning applications in archaeological practices: a review
Deep learning-based synthetic-CT generation in radiotherapy and PET: a review
Response to comment on Mutualism weaken the latitudinal diversity gradient among oceanic islands
Automatic Extraction of Disease Risk Factors from Medical Publications
Deep Learning for Breast MRI Style Transfer with Limited Training Data
Adapting Fake News Detection to the Era of Large Language Models
BanglaBait: Semi-Supervised Adversarial Approach for Clickbait Detection on Bangla Clickbait Dataset
CebuaNER: A New Baseline Cebuano Named Entity Recognition Model
Neural Media Bias Detection Using Distant Supervision With BABE -- Bias Annotations By Experts
Learning Site-specific Styles for Multi-institutional Unsupervised Cross-modality Domain Adaptation
MegActor: Harness the Power of Raw Video for Vivid Portrait Animation
MegActor: Harness the Power of Raw Video for Vivid Portrait Animation
Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution
Content Aware Analysis of Scholarly Networks: A Case Study on CORD19 Dataset
CrudeOilNews: An Annotated Crude Oil News Corpus for Event Extraction
DCT-Net: Domain-Calibrated Translation for Portrait Stylization
Credible, Unreliable or Leaked?: Evidence Verification for Enhanced Automated Fact-checking
On the interaction of automatic evaluation and task framing in headline style transfer
Fighting Fire with Fire: The Dual Role of LLMs in Crafting and Detecting Elusive Disinformation
A Hierarchical Network for Abstractive Meeting Summarization with Cross-Domain Pretraining
PubTables-1M: Towards comprehensive table extraction from unstructured documents
ICME 2025 Grand Challenge on Video Super-Resolution for Video Conferencing
Tunable Convolutions with Parametric Multi-Loss Optimization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.