2026
Learning Realistic Depth via Physics-Grounded Noise Disentanglement with Semantic-Geometric Collaboration
ICML 2026poster
Real-world physical sensing exhibits complex, heterogeneous noise patterns that deviate significantly from idealized simulation, posing a fundamental bottleneck for sim-to-real transfer. Existing sensor modelings typically treat depth noise as a monolithic black-box process, overlooking the distinct…