https://github.com/iesl/CSFCube
공식 코드CSFCube -- A Test Collection of Computer Science Research Articles for Faceted Query by Example
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.
CSFCube -- A Test Collection of Computer Science Research Articles for Faceted Query by Example
StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning
Zero Shot Audio to Audio Emotion Transfer With Speaker Disentanglement
Learnable Data Augmentation for One-Shot Unsupervised Domain Adaptation
NoticIA: A Clickbait Article Summarization Dataset in Spanish
A Preliminary Study of ChatGPT on News Recommendation: Personalization, Provider Fairness, Fake News
EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation
Find the Funding: Entity Linking with Incomplete Funding Knowledge Bases
InstantStyle-Plus: Style Transfer with Content-Preserving in Text-to-Image Generation
Supervised Contrastive Learning for Interpretable Long-Form Document Matching
Metric-Scale Truncation-Robust Heatmaps for 3D Human Pose Estimation
FrameFinder: Explorative Multi-Perspective Framing Extraction from News Headlines
NewsEdits: A News Article Revision Dataset and a Document-Level Reasoning Challenge
Word Embeddings for the Armenian Language: Intrinsic and Extrinsic Evaluation
Nanoscale Microscopy Images Colorization Using Neural Networks
IDCIA: Immunocytochemistry Dataset for Cellular Image Analysis
Unsupervised Image-to-Image Translation with Self-Attention Networks
Sentence Bottleneck Autoencoders from Transformer Language Models
MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs
Empowering NLG: Offline Reinforcement Learning for Informal Summarization in Online Domains
Trouble with the Curve: Predicting Future MLB Players Using Scouting Reports
Linking Social Media Posts to News with Siamese Transformers
ArtBank: Artistic Style Transfer with Pre-trained Diffusion Model and Implicit Style Prompt Bank
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.