https://github.com/kata-ai/indosum
공식 코드IndoSum: A New Benchmark Dataset for Indonesian Text Summarization
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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.
IndoSum: A New Benchmark Dataset for Indonesian Text Summarization
Neural sentence embedding models for semantic similarity estimation in the biomedical domain
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Wiki-Reliability: A Large Scale Dataset for Content Reliability on Wikipedia
Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles
Low-Level Linguistic Controls for Style Transfer and Content Preservation
SAMScore: A Content Structural Similarity Metric for Image Translation Evaluation
ImprovNet -- Generating Controllable Musical Improvisations with Iterative Corruption Refinement
Content based News Recommendation via Shortest Entity Distance over Knowledge Graphs
Keyphrase Generation Beyond the Boundaries of Title and Abstract
Faking Fake News for Real Fake News Detection: Propaganda-loaded Training Data Generation
Tip of the Tongue Query Elicitation for Simulated Evaluation
Tip of the Tongue Query Elicitation for Simulated Evaluation
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
Temporal Consistency Learning of inter-frames for Video Super-Resolution
Fast Differentiable Matrix Square Root and Inverse Square Root
Need is All You Need: Homeostatic Neural Networks Adapt to Concept Shift
Telling Stories for Common Sense Zero-Shot Action Recognition
Monant Medical Misinformation Dataset: Mapping Articles to Fact-Checked Claims
RoFT: A Tool for Evaluating Human Detection of Machine-Generated Text
VCISR: Blind Single Image Super-Resolution with Video Compression Synthetic Data
MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models
GeoLM: Empowering Language Models for Geospatially Grounded Language Understanding
CLIPGaussian: Universal and Multimodal Style Transfer Based on Gaussian Splatting
Reveal the Unknown: Out-of-Knowledge-Base Mention Discovery with Entity Linking
Evons: A Dataset for Fake and Real News Virality Analysis and Prediction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.