7 accepted papers
Myocardial infarction (MI) is one of the most dangerous cardiovascular diseases, typically diagnosed using electrocardiogram (ECG). While many deep learning methods exist for MI detection, they often overlook the correlations and medical knowledge between leads of ECG, resulting in limited interpret…
Existing infrared and visible image fusion methods often face the dilemma of balancing modal information. Generative fusion methods reconstruct fused images by learning from data distributions, but their generative capabilities remain limited. Moreover, the lack of interpretability in modal informat…
To perform target-following tasks in unknown environments, a robot must identify the target’s position and plan an efficient path to reach it. Traditional LiDAR-based localization systems face challenges in distinguishing the target from objects with similar appearances. Meanwhile, existing target-f
Homography estimation is a fundamental task in many computer vision applications. Recently, deep learning-based methods have shown to be favorable for this problem when compared to traditional methods. They typically transform the homography estimation into regressing 4 point offsets which can be us
We observe two phenomenons with respect to quantity and capacity: 1) more teacher is not always better for multi-teacher knowledge distillation, and 2) stronger teacher is not always better for single-teacher knowledge distillation. To trade off the quantity and capacity of teacher ensemble, in this…
In this paper, we propose Stochastic Knowledge Distillation (SKD) to obtain compact BERT-style language model dubbed SKDBERT. In each distillation iteration, SKD samples a teacher model from a pre-defined teacher team, which consists of multiple teacher models with multi-level capacities, to transfe…
Transformer architecture has shown great potential for many visual tasks, including point cloud registration. As an order-aware module, position encoding plays an important role in Transformer architecture applied to point cloud registration task. In this paper, we propose OIF-PCR, a one-inlier base…