Scene understanding under low-light conditions is a challenging problem. This
is due to the small number of photons captured by the camera and the resulting
low signal-to-noise ratio (SNR). single-photon cameras
通过提出一种端到端的非标定多视点 PS 框架,以实现在真实环境中通过稀疏视点获取高分辨率形状的重建,摒弃了黑暗室的假设,并允许静态环境光和动态 LED 光的组合,从而实现了在实验室外轻松捕获数据,并通过实验证实,在稀疏视点情况下超越了现有的基准方法,将高精度三维重建从黑暗室引入到现实世界中,并保持了合理的数据采集复杂性。