Adapting Depth Anything V2 with DV-LORA bridges the ex-vivo to in-vivo gap in monocular depth estimation for specular surgical environments, achieving SOTA on SCARED and superior results on new ROCAL-T 90 dataset.
Kimera-multi: Robust, distributed, dense metric-semantic slam for multi-robot systems
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Bridging the Ex-Vivo to In-Vivo Gap: Synthetic Priors for Monocular Depth Estimation in Specular Surgical Environments
Adapting Depth Anything V2 with DV-LORA bridges the ex-vivo to in-vivo gap in monocular depth estimation for specular surgical environments, achieving SOTA on SCARED and superior results on new ROCAL-T 90 dataset.