Monocular Depth Essentials Monocular Depth Essentials is a lightweight, curated core dataset tailored specifically for Monocular Depth Estimation tasks. Following the data preparation guidelines from the classic bts repository , this dataset extracts only the essential image depth pairs from the massive raw KITTI and NYU Depth V2 datasets based strictly on the official Eigen Split train/test text lists. If you are benchmarking or reproducing Depth Anything (V1/V2) , BTS , or other monocular depth estimation models, this dataset allows you to bypass the tedious raw data downloading, filtering, and cleaning phases, offering a true "plug and play" experience. 📌 Dataset Features & Structure Streamlined Data : Redundant sequences not evaluated in standard benchmarks are excluded, leaving only the exact samples specified by the official txt splits. Standard Evaluation : Fully adheres to the academic standard Eigen Split , ensuring fair and direct experimental comparison. Clean Directory : Organised to seamlessly align with dataloaders in mainstream depth estimation codebases.
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