SCE-Depth: A Spherical Compound Eye Framework for Wide FOV Depth Estimation
Yi Zhu, Hao Xiong, Lin Xiao, Ranfeng Shi, Qinying Gu, Leilei Gu
2026年份
摘要
ent Loss (SGL), which jointly extract gradient features on the HEALPix grid, enabling gradient-aware depth prediction. Extensive benchmark experiments demonstrate that these strategies enable SCE-Depth to substantially reduce depth estimation error compared to fisheye-based baselines, with particularly large improvements in peripheral accuracy. We also demonstrate the generalization capability of SCE-Depth to other wide FOV data modalities, such as fisheye and panoramic imagery. Code is available at https://github.com/ZhuYi2000/SCE-Depth.
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