Mar 20, 2024 · Our model exhibits remarkable generalization capabilities by only training on 63k purely synthetic samples and is capable of zero-shot depth estimation across ...

Aug 11, 2023 · We show that the depth-relative attention bias makes the model more robust in estimating unseen depth ranges. Proceedings of the Thirty-Second International ...

Apr 27, 2024 · This paper discusses the results of the third edition of the Monocular Depth Estimation Challenge (MDEC). The challenge focuses on zero-shot generalization to ...

Sep 26, 2023 · We delve into design considerations for crafting more robust depth estimation models, touching upon pre-training, augmentation, modality, model capacity, and ...

Jun 11, 2024 · This normalization allows. Marigold to focus on pure affine-invariant depth estimation. ... Hierarchical normalization for robust monoc- ular depth estimation.

Apr 3, 2024 · This paper aims to design monocular depth estimation mod- els with better generalization abilities. To this end, we have conducted quantitative analysis and ...

Jul 20, 2023 · Hierarchical Normalization for Robust Monocular Depth Estimation. In this paper, we address monocular depth estimation with deep neural ne... 0 Chi Zhang, et ...

Nov 27, 2023 · Hierarchical normalization for robust monocular depth estimation. C Zhang, W Yin, B Wang, G Yu, B Fu, C Shen. Advances in Neural Information Processing ...

Jan 31, 2024 · A hierarchical layer for refining depth is implemented, which performs high-quality up-sampling for preserving the edges. For the training of the network, the ...

Dec 4, 2023 · Monocular depth estimation is a fundamental computer vision task. Recovering 3D depth ... Hierarchical Normalization for Robust Monocular Depth Estimation · Chi ...