4 papers
GO-Renderer: Generative Object Rendering with 3D-aware Controllable Video Diffusion Models
Zekai Gu, Shuoxuan Feng, Yansong Wang +6
Reconstructing a renderable 3D model from images is a useful but challenging task. Recent feedforward 3D reconstruction methods have demonstrated remarkable success in efficiently…
RefAny3D: 3D Asset-Referenced Diffusion Models for Image Generation
Hanzhuo Huang, Qingyang Bao, Zekai Gu +4
In this paper, we propose a 3D asset-referenced diffusion model for image generation, exploring how to integrate 3D assets into image diffusion models. Existing reference-based ima…
Adaptive Part Learning for Fine-Grained Generalized Category Discovery: A Plug-and-Play Enhancement
Qiyuan Dai, Hanzhuo Huang, Yu Wu +1
Generalized Category Discovery (GCD) aims to recognize unlabeled images from known and novel classes by distinguishing novel classes from known ones, while also transferring knowle…
MVTokenFlow: High-quality 4D Content Generation using Multiview Token Flow
Hanzhuo Huang, Yuan Liu, Ge Zheng +3
In this paper, we present MVTokenFlow for high-quality 4D content creation from monocular videos. Recent advancements in generative models such as video diffusion models and multiv…