5 accepted papers
Transformers have made significant progress in dealing with computer vision tasks. However, most existing Vision Transformers (ViT) typically focus on single-scale information, limiting their capability to model interactions when processing multi-scale features. Moreover, the explicit mapping of con…
3D Gaussian Splatting (3DGS) is gaining popularity in fields such as robotics, autonomous driving, and virtual reality, due to its effectiveness and efficiency. Given that some tasks involve high risks, it is crucial to investigate the adversarial robustness of 3DGS and its downstream tasks—a topic…
Denoising diffusion models have shown great potential in multiple research areas. Existing diffusion-based generative methods on de novo 3D molecule generation face two major challenges. Since majority heavy atoms in molecules allow connections to multiple atoms through single bonds, solely using pa…
Recently, cross-modal hashing has attracted much attention in large-scale image retrieval scenarios. However, most existing methods ignore the potential higher-order relationships and label semantic information between heterogeneous modality data. Besides, the imbalanced training samples could bias…
The surging volume of big data underscores the imperative of integrating heterogeneous datasets into a unified, semantically consistent format. We introduce Pyramid, a comprehensive framework for heterogeneous data integration, addressing schema transformation, feature encoding, entity matching, ded…