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Toward A Better Understanding of Monocular Depth Evaluation
Siyang Wu, Jack Nugent, Willow Yang +1
Monocular depth estimation is an important task with rapid progress, but how to evaluate it is not fully resolved, as evidenced by a lack of standardization in existing literature…
Evaluating Robustness of Monocular Depth Estimation with Procedural Scene Perturbations
Jack Nugent, Siyang Wu, Zeyu Ma +7
Recent years have witnessed substantial progress on monocular depth estimation, particularly as measured by the success of large models on standard benchmarks. However, performance…
What Makes Good Synthetic Training Data for Zero-Shot Stereo Matching?
David Yan, Alexander Raistrick, Jia Deng
Synthetic datasets are a crucial ingredient for training stereo matching networks, but the question of what makes a stereo dataset effective remains underexplored. We investigate t…
LayeredFlow: A Real-World Benchmark for Non-Lambertian Multi-Layer Optical Flow
Hongyu Wen, Erich Liang, Jia Deng
Achieving 3D understanding of non-Lambertian objects is an important task with many useful applications, but most existing algorithms struggle to deal with such objects. One major…
Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generation
Alexander Raistrick, Lingjie Mei, Karhan Kayan +9
We introduce Infinigen Indoors, a Blender-based procedural generator of photorealistic indoor scenes. It builds upon the existing Infinigen system, which focuses on natural scenes,…