DidSee is a diffusion-based depth completion model that combines a zero terminal-SNR noise scheduler, single-step training, and a semantic segmentation enhancer to achieve state-of-the-art results on non-Lambertian objects.
Clearpose: Large-scale trans- parent object dataset and benchmark
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DidSee: Diffusion-Based Depth Completion for Material-Agnostic Robotic Perception and Manipulation
DidSee is a diffusion-based depth completion model that combines a zero terminal-SNR noise scheduler, single-step training, and a semantic segmentation enhancer to achieve state-of-the-art results on non-Lambertian objects.