Swin Transformer V2: Scaling Up Capacity and Resolution
We present techniques for scaling Swin Transformer [35] up to 3 billion parameters and making it capable of training with images of up to 1,536x1,536 resolution. By scaling up c...
Publications
3 shownOscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks
Large-scale pre-training methods of learning cross-modal representations on image-text pairs are becoming popular for vision-language tasks. While existing methods simply concat...
WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
Self-supervised learning (SSL) achieves great success in speech recognition,\nwhile limited exploration has been attempted for other speech processing tasks.\nAs speech signal c...
Frequent Co-Authors
Researcher Info
- h-index
- 3
- Publications
- 3
- Citations
- 4,573
- Institution
- Microsoft Research Asia (China)
External Links
Identifiers
- ORCID
- 0000-0002-7810-5852
Impact Metrics
h-index
3
h-index: Number of publications with at least h citations each.