FasterViT is a new family of hybrid CNN-ViT neural networks
FasterViT combines the benefits of fast local representation learning in CNNs and global modeling properties in ViT
FasterViT achieves a SOTA Pareto-front in terms of accuracy and image throughput
Use Cases where we have deployed solutions:
Visual Question Answering (VQA):
Integrating vision and language models to answer questions based on the content of images, useful in interactive AI applications.
Facial Recognition and Analysis:
Security Systems: Identifying individuals in security and access control systems.
Social Media: Tagging and organizing photos based on recognized faces.
Action Recognition:
Video Analysis: Recognizing actions or activities in video sequences for applications in sports analytics, surveillance, and content recommendation.
Image Generation and Enhancement:
Super-Resolution: Enhancing the resolution of images for better quality.
Image Synthesis: Generating new images for creative applications, data augmentation, or simulating environments.
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