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Found 4 papers, 2 papers with code
MaskingDepth: Masked Consistency Regularization for Semi-supervised Monocular Depth Estimation
We propose MaskingDepth, a novel semi-supervised learning framework for monocular depth estimation to mitigate the reliance on large ground-truth depth quantities.
DAG: Depth-Aware Guidance with Denoising Diffusion Probabilistic Models
Generative models have recently undergone significant advancement due to the diffusion models.
InstaFormer: Instance-Aware Image-to-Image Translation with Transformer
By augmenting such tokens with an instance-level feature extracted from the content feature with respect to bounding box information, our framework is capable of learning an interaction between object instances and the global image, thus boosting the instance-awareness.
Semi-Supervised Learning with Mutual Distillation for Monocular Depth Estimation
We propose a semi-supervised learning framework for monocular depth estimation.
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