6 accepted papers
An end-to-end monocular 3D recovery framework for Deformable Linear Object (DLO) is proposed in this paper. The fragmented and unreliable 3D point clouds caused by the thin profile and reflective surfaces of DLOs when captured with an RGB-D camera have been a critical challenge in 3D DLO perception.
Recent advancements in large language models (LLMs) have shown promising ability to perform commonsense reasoning, bringing machines closer to human-like understanding. However, deciphering the internal reasoning processes of LLMs remains challenging due to the complex interdependencies among genera…
A novel RGB-based continuous perception garment classification approach is proposed in this letter, with the aim of identifying the correct category of the garment from a set of categories. It has been observed that treating a video of the continuous deformation of cloth as a set of disordered stati
Out-of-distribution (OOD) detection is a critical task for ensuring the reliability and safety of deep neural networks in real-world scenarios. Different from most previous OOD detection methods that focus on designing OOD scores or introducing diverse outlier examples to retrain the model, we delve…
Despite the promising progress having been made, the two challenges of multi-view clustering (MVC) are still waiting for better solutions: i) Most existing methods are either not qualified or require additional steps for incomplete multi-view clustering and ii) noise or outliers might significantly…
Tracking for planar objects is an important issue to vision-based robotic applications. In direct visual tracking (DVT) methods, the similarity between two images is often measured through the sum of squared differences (SSD) especially with the efficient second-order minimization (ESM) due to its s…