3 accepted papers
In this paper, we focus on the task of conditional image generation, where an image is synthesized according to user instructions. The critical challenge underpinning this task is ensuring both the fidelity of the generated images and their semantic alignment with the provided conditions. To tackle…
Current robotic systems can understand the categories and poses of objects well. But understanding physical properties like mass, friction, and hardness, in the wild, remains challenging. We propose a new method that reconstructs 3D objects using the Gaussian splatting representation and predicts va
Recognizing objects in the 3D world is a significant challenge for robotics. Due to the lack of high-quality 3D data, directly training a general-purpose segmentation model in 3D is almost infeasible. Meanwhile, vision foundation models (VFM) have revolutionized the 2D computer vision field with out