4 accepted papers
The reliability of autonomous systems in real-world environments is mainly dependent on the robustness of their visual perception.Although recent studies have advanced the handling of visual degradations, physical contaminants that adhere to the camera lens--such as mud, water droplets, and condensa
Robotic manipulation in embodied AI critically depends on large-scale, high-quality datasets that reflect realistic object interactions and physical dynamics. However, existing data collection pipelines are often slow, expensive, and heavily reliant on manual efforts. We present DynScene, a diffusio…
Smartphone cameras are ubiquitous in daily life, yet their performance can be severely impacted by dirty lenses, leading to degraded image quality. This issue is often overlooked in image restoration research, which assumes ideal or controlled lens conditions. To address this gap, we introduced SI…
Domain randomization (DR) is a powerful tool to make a policy robust to the uncertainty of dynamics caused by unobservable environmental parameters. Conventional DR has adopted model-free reinforcement learning as a policy optimizer. However, the model-free methods in DR demand high time-complexity…