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cs.CV2025
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…
cs.RO2025
Procedural Generation of Articulated Simulation-Ready Assets
Abhishek Joshi, Beining Han, Jack Nugent +12
We introduce Infinigen-Articulated, a toolkit for generating realistic, procedurally generated articulated assets for robotics simulation. We include procedural generators for 18 c…
cs.CV2025
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…