Mureka是首个将AI音乐生成、编辑和版权交易结合在一起的平台，旨在帮助每位创作者捕捉灵感，利用AI技术转化为高质量音乐作品。
Mureka的特点:
- 1. 集成AI音乐生成与编辑功能
- 2. 提供音乐版权交易服务
- 3. 支持多种音乐风格与格式
- 4. 用户友好的界面，便于操作
- 5. 高质量的音频输出
Mureka的功能:
- 1. 创作原创音乐作品
- 2. 编辑已有音乐，添加特效
- 3. 交易音乐版权，获取收益
- 4. 与其他音乐人合作，共同创作
相关导航
Nname: “SimVP: Simpler yet Better Video Prediction” description: “A simpler yet more effective approach for video prediction.” url: “https://github.com/gaozhangyang/SimVP-Simpler-yet-Better-Video-Prediction” features: – “Simpler architecture for video prediction.” – “Improved accuracy in generated video frames.” usage: – “Used in video analysis and prediction tasks.” – “Applicable in autonomous driving for motion forecasting.” name: “A Brand New Dance Partner: Music-Conditioned Pluralistic Dancing Synthesized by Multiple Dance Genres” description: “Generates dance movements based on music and multiple dance genres.” url: “https://github.com/jw09191/MNET” features: – “Music-conditioned dance generation.” – “Supports multiple dance genres.” usage: – “Used in entertainment for creating dance performances.” – “Applicable in game development for character animations.” name: “Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries” description: “A framework for continual learning in contaminated data streams.” url: “https://github.com/clovaai/puridiver” features: – “Handles contaminated data effectively.” – “Learns continuously with blurry task boundaries.” usage: – “Used in applications requiring ongoing learning from data streams.” – “Applicable in real-time systems where data quality varies.” name: “Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition” description: “A transformer-based model for scene text recognition.” url: “https://github.com/xdxie/WordArt” features: – “Corner-guided attention mechanism.” – “Improved accuracy in recognizing scene text.” usage: – “Used in OCR applications for extracting text from images.” – “Applicable in augmented reality for real-time text recognition.” name: “Masked Discrimination for Self-Supervised Learning on Point Clouds” description: “Self-supervised learning approach for point clouds.” url: “https://github.com/haotian-liu/MaskPoint” features: – “Utilizes masked discrimination for better learning.” – “Effective for point cloud data.” usage: – “Used in 3D object recognition tasks.” – “Applicable in robotics for understanding spatial environments.” name: “Egocentric Scene Reconstruction from an Omnidirectional Video” description: “Reconstructs scenes from omnidirectional video data.” url: “https://github.com/KAIST-VCLAB/EgocentricReconstruction” features: – “Reconstructs 3D scenes from 2D video.” – “Utilizes omnidirectional video for complete scene capture.” usage: – “Used in virtual reality applications for immersive experiences.” – “Applicable in surveillance for environment reconstruction.” name: “Spelunking the Deep: Guaranteed Queries for General Neural Implicit Surfaces via Range Analysis” description: “A method for querying neural implicit surfaces.” url: “https://github.com/nmwsharp/neural-implicit-queries” features: – “Provides guaranteed queries for neural surfaces.” – “Utilizes range analysis for improved accuracy.” usage: – “Used in computer graphics for surface representation.” – “Applicable in 3D modeling and rendering tasks.” name: “InCloud: Incremental Learning for Point Cloud Place Recognition” description: “Incremental learning framework for point cloud recognition.” url: “https://github.com/csiro-robotics/InCloud” features: – “Supports incremental learning.” – “Effective for place recognition using point clouds.” usage: – “Used in robotic navigation and mapping.” – “Applicable in augmented reality for environment understanding.” name: “DETRs with Hybrid Matching” description: “Enhances DETR with hybrid matching for object detection.” url: “https://github.com/HDETR/H-Deformable-DETR” features: – “Hybrid matching mechanism for improved detection.” – “Enhances the performance of DETR.” usage: – “Used in object detection tasks in images.” – “Applicable in autonomous systems for real-time object tracking.” name: “Few-shot Adaptation Works with UnpredicTable Data” description: “Framework for few-shot learning with unpredictable data.” url: “https://github.com/JunShern/few-shot-adaptation” features: – “Adapts well to few-shot learning scenarios.” – “Handles unpredictable data effectively.” usage: – “Used in scenarios with limited labeled data.” – “Applicable in personalized AI applications.” name: “Large-Scale Product Retrieval with Weakly Supervised Representation Learning” description: “Product retrieval system using weakly supervised learning.” url: “https://github.com/01BB01/eBayChallenge” features: – “Large-scale product retrieval capabilities.” – “Weakly supervised representation learning.” usage: – “Used in e-commerce for product search.” – “Applicable in recommendation systems for suggesting products.” name: “Accurate Polygonal Mapping of Buildings in Satellite Imagery” description: “Maps buildings accurately from satellite images.” url: “https://github.com/SarahwXU/HiSup” features: – “High accuracy in building mapping.” – “Utilizes satellite imagery for data.” usage: – “Used in urban planning and development.” – “Applicable in environmental monitoring.” name: “HHP-Net: A light Heteroscedastic neural network for Head Pose estimation with uncertainty” description: “A lightweight neural network for head pose estimation.” url: “https://github.com/cantarinigiorgio/HHP-Net” features: – “Lightweight architecture for efficiency.” – “Estimates head pose with uncertainty measures.” usage: – “Used in human-computer interaction.” – “Applicable in driver monitoring systems.” name: “A Dual-Masked Auto-Encoder for Robust Motion Capture with Spatial-Temporal Skeletal Token Completion” description: “Auto-encoder for robust motion capture data processing.” url: “https://github.com/HKBU-VSComputing/2022_MM_DMAE-Mocap” features: – “Dual-masked auto-encoder architecture.” – “Handles spatial-temporal data effectively.” usage: – “Used in motion capture systems.” – “Applicable in animation and gaming.” name: “Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions” description: “Model for RNA structure and function predictions.” url: “https://github.com/ml4bio/RNA-FM” features: – “Interpretable predictions for RNA data.” – “Highly accurate structure and function predictions.” usage: – “Used in bioinformatics for RNA analysis.” – “Applicable in drug discovery and development.” name: “A Benchmarking Initiative for Audio-Domain Music Generation Using the Freesound Loop Dataset” description: “Initiative for benchmarking music generation in audio domain.” url: “https://github.com/naotokui/LoopGAN” features: – “Benchmarking framework for music generation.” – “Utilizes Freesound Loop Dataset.” usage: – “Used in music generation applications.” – “Applicable in audio synthesis and production.”-音频领域音乐生成基准测试
在音频领域内进行音乐生成的基准测试项目，利用Freesound Loop数据集。
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