Presents the first large-scale benchmark for multi-frame geometric distortion removal in videos under severe refractive warping, using real and synthetic data across four distortion levels and evaluating classical and learning-based methods including a proposed diffusion-based V-cache.
Adding conditional control to text-to-image diffusion models
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Marigold-SSD delivers zero-shot depth completion via single-step diffusion with late fusion, achieving fast inference after only 4.5 GPU days of training while showing strong cross-domain results on indoor and outdoor benchmarks.
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A unified Benchmark for Multi-Frame Image Restoration under Severe Refractive Warping
Presents the first large-scale benchmark for multi-frame geometric distortion removal in videos under severe refractive warping, using real and synthetic data across four distortion levels and evaluating classical and learning-based methods including a proposed diffusion-based V-cache.
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Need for Speed: Zero-Shot Depth Completion with Single-Step Diffusion
Marigold-SSD delivers zero-shot depth completion via single-step diffusion with late fusion, achieving fast inference after only 4.5 GPU days of training while showing strong cross-domain results on indoor and outdoor benchmarks.