7 accepted papers
Achieving natural, robust, and energy-efficient locomotion remains a central challenge for humanoid control. While imitation learning enables robots to reproduce human-like behaviors, differences in morphology, actuation, and partial observability often limit direct motion replication. This work pro
Large language models (LLMs) often struggle with context fidelity, producing inconsistent answers when responding to questions based on provided information. Existing approaches either rely on expensive supervised fine-tuning to generate evidence post-answer or train models to perform web searches w
Multiple rotation averaging plays a crucial role in computer vision and robotics domains. The conventional optimization-based methods optimize a nonlinear cost function based on certain noise assumptions, while most previous learning-based methods require ground truth labels in the supervised traini
The majority of point cloud registration methods currently rely on extracting features from points. However, these methods are limited by their dependence on information obtained from a single modality of points, which can result in deficiencies such as inadequate perception of global features and a
As a fundamental problem in computer vision, point cloud registration aims to seek the optimal transformation for aligning a pair of point clouds. In most existing methods, the information flows are usually forward transferring, thus lacking the guidance from high-level information to low-level info
Multiview point cloud registration plays a crucial role in robotics, automation, and computer vision fields. This letter concentrates on pose graph construction and motion synchronization within multiview registration. Previous methods for pose graph construction often pruned fully connected graphs
Haze is one of the most important factors which reduce the outdoor image quality. Existing approaches often aim to design their models based on principles of hazes. However, even with exactly modeled haze distribution, it is still a challenging task due to factors in real scenario, such as noises, h…