pixel-correspondence

This paper proposes VLM3, a method that adapts vision language models for 3D understanding tasks through simple architectural modifications and text-based training, achieving competitive performance without complex designs. It demonstrates significant improvements in depth estimation accuracy and enables diverse 3D tasks like pixel correspondence, camera pose estimation, and object-level understanding.