7 accepted papers
Few-shot Font Generation (FFG) aims to create a complete font from a limited number of references, offering significant practical value. However, existing methods neglect glyph spatial information, which leads to two critical limitations. At the pipeline level, distorted rendering introduces spatial
Previous multi-view contrastive learning methods typically operate at two scales: instance-level and cluster-level. The former generally constructs positive and negative pairs based on the correspondence between samples and view instances. These methods aim to bring positive pairs closer and push…
Multi-view clustering has been widely explored for its effectiveness in harmonizing heterogeneity along with consistency in different views of data. Despite the significant progress made by recent works, the performance of most existing methods is heavily reliant on strong priori information regardi…
Model adaptation is crucial to handle the discrepancy between proxy training data and actual users’ data received. To effectively perform adaptation, textual data of users is typically stored on servers or their local devices, where downstream natural language processing (NLP) models can be directly…
Multi-view kernel clustering (MKC) aims to fully reveal the consistency and complementarity of multiple views in a potential Hilbert space, thereby enhancing clustering performance. The clustering results of most MKC methods are highly sensitive to the quality of the constructed kernels, as traditio…
Human beings can quickly adapt to environmental changes by leveraging learning experience. However, adapting deep neural networks to dynamic environments by machine learning algorithms remains a challenge. To better understand this issue, we study the problem of continual domain adaptation, where t…
Real-world object detectors are often challenged by the domain gaps between different datasets. In this work, we present the Conditional Domain Normalization (CDN) to bridge the domain distribution gap. CDN is designed to encode different domain inputs into a shared latent space, where the features…