Data Augmentation and Optimized Architectures for Computer Vision with Fatih Porikli - #635

This article summarizes a discussion with Fatih Porikli, a Senior Director at Qualcomm, about the 2023 CVPR conference. The conversation covered 12 papers/demos, focusing on data augmentation and optimized architectures for computer vision. Key topics included advancements in optical flow estimation, cross-model and stage knowledge distillation for 3D object detection, and zero-shot learning using language models. The discussion also touched on generative AI, computer vision optimization for edge devices, objective functions, neural network architecture design, and efficiency/accuracy improvements in AI models. The article provides a high-level overview of cutting-edge research in computer vision.

• •The discussion highlights advancements in data augmentation techniques for computer vision.
• •Optimized architectures for running large AI models on edge devices are a key focus.
• •The article covers a range of topics including object detection, zero-shot learning, and generative AI.