https://github.com/pixelite1201/agora_evaluation
공식 코드AGORA: Avatars in Geography Optimized for Regression Analysis
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.
AGORA: Avatars in Geography Optimized for Regression Analysis
Synthetic Data Generation with Large Language Models for Personalized Community Question Answering
ArtFlow: Unbiased Image Style Transfer via Reversible Neural Flows
Match-Ignition: Plugging PageRank into Transformer for Long-form Text Matching
Align then Summarize: Automatic Alignment Methods for Summarization Corpus Creation
Wiki-CS: A Wikipedia-Based Benchmark for Graph Neural Networks
Linking Named Entities in Diderot's \textit{Encyclopédie} to Wikidata
LLM Attributor: Interactive Visual Attribution for LLM Generation
LLM Attributor: Interactive Visual Attribution for LLM Generation
Differentially Private Adaptation of Diffusion Models via Noisy Aggregated Embeddings
Check-COVID: Fact-Checking COVID-19 News Claims with Scientific Evidence
Stance Detection in Web and Social Media: A Comparative Study
Predictive analysis of Bitcoin price considering social sentiments
0-MMS: Zero-Shot Multi-Motion Segmentation With A Monocular Event Camera
LitSearch: A Retrieval Benchmark for Scientific Literature Search
Efficient, Self-Supervised Human Pose Estimation with Inductive Prior Tuning
Do LSTMs See Gender? Probing the Ability of LSTMs to Learn Abstract Syntactic Rules
Distinguish Confusion in Legal Judgment Prediction via Revised Relation Knowledge
Distinguish Confusing Law Articles for Legal Judgment Prediction
Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference
StyleCLIPDraw: Coupling Content and Style in Text-to-Drawing Synthesis
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.