WildDepth: A Multimodal Dataset for 3D Wildlife Perception and Depth Estimation

ArXi:2603.16816v1 Announce Type: new Depth estimation and 3D reconstruction have been extensively studied as core topics in computer vision. Starting from rigid objects with relatively simple geometric shapes, such as vehicles, the research has expanded to address general objects, including challenging deformable objects, such as humans and animals. However, for the animal, in particular, the majority of existing models are trained based on datasets without metric scale, which can help validate image-only models.