4 accepted papers
Unlike closed-vocabulary 3D instance segmentation that is often trained end-to-end, open-vocabulary 3D instance segmentation (OV-3DIS) often leverages vision-language models (VLMs) to generate 3D instance proposals and classify them. While various concepts have been proposed from existing research,…
6D object pose estimation has shown strong generalizability to novel objects. However, existing methods often require either a complete, well-reconstructed 3D model or numerous reference images that fully cover the object. Estimating 6D poses from partial references, which capture only fragments of…
This paper addresses the challenge of reconstructing a scene with a neural radiance field (NeRF) for robot vision and scene understanding using multiple modalities. Researchers have introduced the use of NeRF to represent an object for synthesizing and rendering novel views of complex scenes by opti…
Learning to recognize objects based on names is a crucial capability for personal robots. Recent recognition methods successfully learn to recognize objects in a train-once-then-test setting. Yet, these methods do not apply readily to robotic settings, where a robot might continuously encounter new