5 papers · 1 filter
Perceptual Flow Matching for Few-Step Generative Modeling
Chuyang Zhao, Yifei Song, Hongfa Wang +7
We propose Perceptual Flow Matching (PFM), a simple yet effective framework for few-step generation in flow-matching models. Rather than performing velocity regression in the conve…
Improving Text-guided Object Inpainting with Semantic Pre-inpainting
Yifu Chen, Jingwen Chen, Yingwei Pan +4
Recent years have witnessed the success of large text-to-image diffusion models and their remarkable potential to generate high-quality images. The further pursuit of enhancing the…
DreamMesh: Jointly Manipulating and Texturing Triangle Meshes for Text-to-3D Generation
Haibo Yang, Yang Chen, Yingwei Pan +5
Learning radiance fields (NeRF) with powerful 2D diffusion models has garnered popularity for text-to-3D generation. Nevertheless, the implicit 3D representations of NeRF lack expl…
Hi3D: Pursuing High-Resolution Image-to-3D Generation with Video Diffusion Models
Haibo Yang, Yang Chen, Yingwei Pan +4
Despite having tremendous progress in image-to-3D generation, existing methods still struggle to produce multi-view consistent images with high-resolution textures in detail, espec…
FreeEnhance: Tuning-Free Image Enhancement via Content-Consistent Noising-and-Denoising Process
Yang Luo, Yiheng Zhang, Zhaofan Qiu +4
The emergence of text-to-image generation models has led to the recognition that image enhancement, performed as post-processing, would significantly improve the visual quality of…