https://github.com/haha-lisa/CreativeSynth
공식 코드CreativeSynth: Cross-Art-Attention for Artistic Image Synthesis with Multimodal Diffusion
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.
CreativeSynth: Cross-Art-Attention for Artistic Image Synthesis with Multimodal Diffusion
DiffStyler: Controllable Dual Diffusion for Text-Driven Image Stylization
Style-A-Video: Agile Diffusion for Arbitrary Text-based Video Style Transfer
TSSAT: Two-Stage Statistics-Aware Transformation for Artistic Style Transfer
KhabarChin: Automatic Detection of Important News in the Persian Language
SliceNDice: Mining Suspicious Multi-attribute Entity Groups with Multi-view Graphs
Learning Hierarchical Discourse-level Structure for Fake News Detection
Learning Hierarchical Discourse-level Structure for Fake News Detection
Quality Evaluation of Arbitrary Style Transfer: Subjective Study and Objective Metric
Cross-lingual Transfer Learning for Fake News Detector in a Low-Resource Language
TATA: Stance Detection via Topic-Agnostic and Topic-Aware Embeddings
Stain Style Transfer of Histopathology Images Via Structure-Preserved Generative Learning
AudioLDM: Text-to-Audio Generation with Latent Diffusion Models
Intelligent Grimm -- Open-ended Visual Storytelling via Latent Diffusion Models
Auffusion: Leveraging the Power of Diffusion and Large Language Models for Text-to-Audio Generation
BioNerFlair: biomedical named entity recognition using flair embedding and sequence tagger
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation
Greedy Offset-Guided Keypoint Grouping for Human Pose Estimation
Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-Resolution
XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
Time-of-Day Neural Style Transfer for Architectural Photographs
NeuS: Neutral Multi-News Summarization for Mitigating Framing Bias
Harvey Mudd College at SemEval-2019 Task 4: The Clint Buchanan Hyperpartisan News Detector
GPT Struct Me: Probing GPT Models on Narrative Entity Extraction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.