Self-Supervised Noise Embeddings (Self-SNE)
Self-Supervised Metric Learning of Blood Cells
ICASSP 2023-2024 Papers: A complete collection of influential and exciting research papers from the ICASSP 2023-24 conferences. Explore the latest advancements in acoustics, speech and signal processing. Code included. Star the repository to support the advancement of audio and signal processing!
CVPR 2023-2024 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. ⭐ support visual intelligence development!
A python library for self-supervised learning on images.
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Self-Supervised Vision Transformers for multiplexed imaging datasets
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
The code repository for the paper: Peijie et al., Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering. IEEE TKDE, 2023.
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. arXiv:2307.09218.
LibAUC: A Deep Learning Library for X-Risk Optimization
Open source Python library for building bioimage analysis pipelines
[Bioinformatics 2022] Cross-Modality and Self-Supervised Protein Embedding for Compound-Protein Affinity and Contact Prediction
[WACV 2024 Oral] - ARNIQA: Learning Distortion Manifold for Image Quality Assessment
[BMVC 2022] This is the official code of our Paper "Revisiting Self-Supervised Contrastive Learning for Facial Expression Recognition"
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
A comprehensive list [SAMRS@NeurIPS'23, RVSA@TGRS'22, RSP@TGRS'22] of our research works related to remote sensing, including papers, codes, and citations. Note: The repo for [TGRS'22] "An Empirical Study of Remote Sensing Pretraining" has been moved to: https://github.com/ViTAE-Transformer/RSP
An optimized implementation of masked autoencoders (MAEs)
[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
Masked Modeling Duo: Towards a Universal Audio Pre-training Framework
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