A 360-degree (omni-directional) image provides an all-encompassing spher...
In recent years, cross-modal domain adaptation has been studied on the p...
Text-conditional diffusion models are able to generate high-fidelity ima...
Pseudo-labels are widely employed in weakly supervised 3D segmentation t...
Classifier-free guidance is an effective sampling technique in diffusion...
Existing multimodal conditional image synthesis (MCIS) methods generate
...
The advent of open-source AI communities has produced a cornucopia of
po...
In this study, we investigate the task of few-shot Generative Domain
Ada...
Font generation is a difficult and time-consuming task, especially in th...
The recently developed discrete diffusion models perform extraordinarily...
Text-guided diffusion models have shown superior performance in image/vi...
Multi-modal reasoning in visual question answering (VQA) has witnessed r...
Few-shot part segmentation aims to separate different parts of an object...
Recently, significant progress has been made in masked image modeling to...
Image paragraph captioning aims to describe a given image with a sequenc...
Quantum computers are next-generation devices that hold promise to perfo...
We present a method that achieves state-of-the-art results on challengin...
Concept learning constructs visual representations that are connected to...
Real-world dynamic scene deblurring has long been a challenging task sin...
Attention mechanisms have been very popular in deep neural networks, whe...
Video frame interpolation, which aims to synthesize non-exist intermedia...
Although conceptualization has been widely studied in semantics and know...
Mild cognitive impairment (MCI) conversion prediction, i.e., identifying...
Quantum machine learning is expected to be one of the first practical
ap...
Dynamic scene blurring is an important yet challenging topic. Recently, ...
Understanding what online users may pay attention to is key to content
r...
Concepts embody the knowledge of the world and facilitate the cognitive
...
Generative adversarial networks (GAN) have been effective for learning
g...
In this paper, we propose a principled Perceptual Adversarial Networks (...