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Current single-view mesh reconstruction methods falter under robot camera rotations, leading to critical errors in spatial reasoning.
Grasping performance can be dramatically improved with a single view adjustment that leverages affordance fields, bypassing the need for complex scene reconstruction.
Nonlinear tone mappings can boost low-light 3D reconstruction quality by over 4 dB, challenging the efficacy of traditional linear methods.