Sphere-Depth: A Benchmark for Depth Estimation Methods with Varying Spherical Camera Orientations

ArXi:2604.23432v1 Announce Type: new Reliable depth estimation from spherical images is crucial for 360{\deg} vision in robotic navigation and immersive scene understanding. However, the onboard spherical camera can experience unintentional pose variations in real-world robotic platforms that, along with the geometric distortions inherent in equirectangular projections, significantly impact the effectiveness of depth estimation. To study this issue, a novel public benchmark, called Sphere-Depth, is