As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

Perceiving the similarity between images has been a long-standing and fundamental
problem underlying various visual generation tasks. Predominant approaches measure the …

Abstract Text-to-image (T2I) research has grown explosively in the past year owing to the
large-scale pre-trained diffusion models and many emerging personalization and editing …

Image inpainting is an underdetermined inverse problem, which naturally allows diverse
contents to fill up the missing or corrupted regions realistically. Prevalent approaches using …

Exemplar-based image translation establishes dense correspondences between a
conditional input and an exemplar (from two different domains) for leveraging detailed …

Deep generative models have achieved conspicuous progress in realistic image synthesis
with multifarious conditional inputs, while generating diverse yet high-fidelity images …

Illumination estimation from a single image is critical in 3D rendering and it has been
investigated extensively in the computer vision and computer graphic research community …

Image inpainting aims to complete the missing or corrupted regions of images with realistic
contents. The prevalent approaches adopt a hybrid objective of reconstruction and …

Accurate lighting estimation is challenging yet critical to many computer vision and computer
graphics tasks such as high-dynamic-range (HDR) relighting. Existing approaches model …

One key challenge of exemplar-guided image generation lies in establishing fine-grained
correspondences between input and guided images. Prior approaches, despite the …