![Google presents groundbreaking AI advancements at CVPR 2023 – Google AI Blog Google presents groundbreaking AI advancements at CVPR 2023 – Google AI Blog](https://aiheadliner.com/wp-content/uploads/https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjna9ws3HEBS4wd_UsuPUR1OMmrdGD8agFbkXjiv9Y2yAKkwAGUgGOOdvqQZESTsNRLHhj0Wj8ZCtKpIGhkR0SrwielzXijpCIr57s_n6EobR8Vry_h6x2B7cAWtiB0obvEyJ098j5K2pYFdjgUdN-vhmC17aSkx-dkseTblY3VGhjWHBZ7G_D7n8pYqw/w1200-h630-p-k-no-nu/CVPR%20Design-hero.jpg)
Google Research is participating in the premier annual Computer Vision and Pattern Recognition conference (CVPR 2023) in Vancouver, BC. They are a Platinum Sponsor and have a strong presence at the conference with 90 papers being presented and participation in over 40 workshops and tutorials.
If you’re attending CVPR this year, make sure to visit Google Research’s booth. Their researchers will be there to discuss the latest techniques in machine perception and showcase recent projects like on-device ML applications with MediaPipe, strategies for differential privacy, neural radiance field technologies, and more.
Here are some of the research projects being presented at CVPR 2023:
1. AligNeRF: High-Fidelity Neural Radiance Fields via Alignment-Aware Training
2. BlendFields: Few-Shot Example-Driven Facial Modeling
3. Enhancing Deformable Local Features by Jointly Learning to Detect and Describe Keypoints
4. How Can Objects Help Action Recognition?
5. Hybrid Neural Rendering for Large-Scale Scenes with Motion Blur
6. IFSeg: Image-Free Semantic Segmentation via Vision-Language Model
7. Learning from Unique Perspectives: User-Aware Saliency Modeling
8. MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis
9. NeRF-Supervised Deep Stereo
10. Omnimatte3D: Associating Objects and their Effects in Unconstrained Monocular Video
These are just a few examples of the exciting research being presented at CVPR 2023. Make sure to check out Google’s booth and learn more about their cutting-edge work in computer vision and machine perception.