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Found 4 papers, 2 papers with code
Language-Based Depth Hints for Monocular Depth Estimation
In this work, we demonstrate the use of natural language as a source of an explicit prior about the structure of the world.
Learning to Project for Cross-Task Knowledge Distillation
In this setting, cross-task distillation can be used, enabling the use of any teacher model trained on a different task.
ObjCAViT: Improving Monocular Depth Estimation Using Natural Language Models And Image-Object Cross-Attention
While monocular depth estimation (MDE) is an important problem in computer vision, it is difficult due to the ambiguity that results from the compression of a 3D scene into only 2 dimensions.
Monocular Depth Estimation Using Cues Inspired by Biological Vision Systems
Part of the MDE task is, therefore, to learn which visual cues in the image can be used for depth estimation, and how.
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