The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

Score distillation sampling (SDS) has shown great promise in text-to-3D generation by
distilling pretrained large-scale text-to-image diffusion models, but suffers from over …

Finding correspondences between images is a fundamental problem in computer vision. In
this paper, we show that correspondence emerges in image diffusion models without any …

We present Magic123, a two-stage coarse-to-fine approach for high-quality, textured 3D
meshes generation from a single unposed image in the wild using both2D and 3D priors. In …

Novel view synthesis from limited observations remains a crucial and ongoing challenge. In
the realm of NeRF-based few-shot view synthesis, there is often a trade-off between the …

Despite recent advances in text-to-3D generative methods there is a notable absence of
reliable evaluation metrics. Existing metrics usually focus on a single criterion each such as …

Denoising diffusion models are a powerful type of generative models used to capture
complex distributions of real-world signals. However, their applicability is limited to …

We present a method for text-driven perpetual view generation--synthesizing long-term
videos of various scenes solely, given an input text prompt describing the scene and camera …

Abstract 3D asset generation is getting massive amounts of attention inspired by the recent
success on text-guided 2D content creation. Existing text-to-3D methods use pretrained text …

Recent years have witnessed remarkable advances in artificial intelligence generated
content (AIGC), with diverse input modalities, eg, text, image, video, audio and 3D. The 3D is …