Single image 3D reconstruction is an important but challenging task that requires extensive
knowledge of our natural world. Many existing methods solve this problem by optimizing a …

Large-scale pre-trained diffusion models have exhibited remarkable capabilities in diverse
video generations. Given a set of video clips of the same motion concept, the task of Motion …

In the realm of digital creativity, our potential to craft intricate 3D worlds from imagination is
often hampered by the limitations of existing digital tools, which demand extensive expertise …

Existing image editing tools, while powerful, typically disregard the underlying 3D geometry
from which the image is projected. As a result, edits made using these tools may become …

We present a novel alignment-before-generation approach to tackle the challenging task of
generating general 3D shapes based on 2D images or texts. Directly learning a conditional …

Many fine-grained classification tasks, like rare animal identification, have limited training
data and consequently classifiers trained on these datasets often fail to generalize to …

We are witnessing a novel era of creativity where anyone can create digital content via
prompt-based learning (known as prompt engineering). This article investigates prompt …

Text-to-image diffusion models are now capable of generating images that are often
indistinguishable from real images. To generate such images, these models must …

Text-conditioned image generation models often generate incorrect associations between
entities and their visual attributes. This reflects an impaired map** between linguistic …

Natural image matting algorithms aim to predict the transparency map (alpha-matte) with the
trimap guidance. However, the production of trimap often requires significant labor, which …