11 accepted papers
Thermal imaging, with its all-weather capabilities and strong penetration, enables 3D reconstruction in low- light and adverse conditions. In this paper, we investigate RGB-independent pure 3D thermal reconstruction, aiming to overcome the challenges of 3D reconstruction in extreme environments wher…
Variational autoencoder performs well in community detection on static networks, but it is difficult to directly extend to continuous dynamic networks. The main reason is that traditional methods mainly rely on adjacency structures to complete the inference and generation processes. However, continu…
Advanced diffusion models like Stable Diffusion 3, Omost, and FLUX have made notable strides in compositional text-to-image generation. However, these methods typically exhibit distinct strengths for compositional generation, with some excelling in handling attribute binding and others in spatial re…
Performance of trimap-free image matting methods is limited when trying to decouple the deterministic and undetermined regions, especially in the scenes where foregrounds are semantically ambiguous, chromaless, or high transmittance. In this paper, we propose a novel framework named Privileged Prior…
Diffusion models have achieved remarkable advancements in text-to-image generation. However, existing models still have many difficulties when faced with multiple-object compositional generation. In this paper, we propose ***RealCompo***, a new *training-free* and *transferred-friendly* text-to-imag…
Most existing portrait matting models either require expensive auxiliary information or try to decompose the task into sub-tasks that are usually resource-hungry. These challenges limit its application on low-power computing devices. In this paper, we propose an ultra-light-weighted portrait matting…
Instance-level feature matching is significantly important to the success of modern one-shot object detectors. Recently, the methods based on the metric-learning paradigm have achieved an impressive process. Most of these works only measure the relations between query and target objects on a single…
Many soft robots are made of hyperelastic silicone rubbers and usually experience large nonlinear deformations in actions. Accurate material parameters are essential to provide reliable analysis and support robot designs. This letter presents a practical material parameter determination method by it
In this letter, we present an approach to study the behavior of compliant plates in granular media and optimize the performance of a robot that utilizes this technique for mobility. From previous work and fundamental tests on thin plate force generation inside granular media, we introduce an origami
With the development of deep convolutional neural networks, image matting has ushered in a new phase. Regarding the nature of image matting, most researches have focused on solutions for transition regions. However, we argue that many existing approaches are excessively focused on transition-dominan…
Information theoretical based methods have attracted a great attention in recent years, and gained promising results to deal with multi-label data with high dimensionality. However, most of the existing methods are either directly transformed from heuristic single-label feature selection methods or…