A Review of 3D Object Detection with Vision-Language Models
Ranjan Sapkota, Konstantinos I Roumeliotis, Rahul Harsha Cheppally, Marco Flores Calero, Manoj Karkee
2025-04-30
Summary
This paper talks about how AI systems can be used to recognize and understand 3D objects by combining what they see in images with what they know from language.
What's the problem?
Detecting 3D objects is hard for AI because it has to figure out shapes and positions from pictures, and it's even trickier when trying to connect that information with words or descriptions.
What's the solution?
The researchers looked at different ways AI models have tried to solve this problem, comparing how well each method works and pointing out what still needs to be improved in the future.
Why it matters?
This matters because better 3D object detection could help with things like self-driving cars, robotics, and virtual reality, making technology smarter and safer in the real world.
Abstract
A systematic review of 3D object detection using vision-language models highlights challenges, compares architectures, and discusses future research directions.