3 accepted papers
Large-scale text-to-image generative models have demonstrated remarkable success in generating diverse and high-quality faces. However, current methods for face editing often unintentionally modify facial features that are intended to be preserved. Multi-step denoising methods necessitate storing mu…
Visual Semantic Embedding (VSE) is a dominant method for cross-modal vision-language retrieval. Its purpose is to learn an embedding space so that visual data can be embedded in a position close to the corresponding text description. However, there are large intra-class variations in the vision-lang…
Video retrieval is a challenging research topic bridging the vision and language areas and has attracted broad attention in recent years. Previous works have been devoted to representing videos by directly encoding from frame-level features. In fact, videos consist of various and abundant semantic r…