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Recent advances in 3D content creation mostly leverage optimization-based 3D generation via score distillation sampling (SDS). Though promising results have been exhibited, these methods often suffer from slow per-sample optimization,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jiaxiang Tang , Jiawei Ren , Hang Zhou , Ziwei Liu , Gang Zeng

We present EucliDreamer, a simple and effective method to generate textures for 3D models given text prompts and meshes. The texture is parametrized as an implicit function on the 3D surface, which is optimized with the Score Distillation…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Cindy Le , Congrui Hetang , Chendi Lin , Ang Cao , Yihui He

Recent text-to-image models, such as Stable Diffusion, have achieved impressive visual quality, yet they often suffer from geometric inconsistencies that undermine the structural realism of generated scenes. One prominent issue is vanishing…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Ryota Okumura , Kaede Shiohara , Toshihiko Yamasaki

Given a 3D mesh, we aim to synthesize 3D textures that correspond to arbitrary textual descriptions. Current methods for generating and assembling textures from sampled views often result in prominent seams or excessive smoothing. To tackle…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Dong Huo , Zixin Guo , Xinxin Zuo , Zhihao Shi , Juwei Lu , Peng Dai , Songcen Xu , Li Cheng , Yee-Hong Yang

Mesh models have become increasingly accessible for numerous cities; however, the lack of realistic textures restricts their application in virtual urban navigation and autonomous driving. To address this, this paper proposes MeSS…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Xuyang Chen , Zhijun Zhai , Kaixuan Zhou , Zengmao Wang , Jianan He , Dong Wang , Yanfeng Zhang , mingwei Sun , Rüdiger Westermann , Konrad Schindler , Liqiu Meng

Current text-to-3D generation methods based on score distillation often suffer from geometric inconsistencies, leading to repeated patterns across different poses of 3D assets. This issue, known as the Multi-Face Janus problem, arises…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Chenxi Zheng , Yihong Lin , Bangzhen Liu , Xuemiao Xu , Yongwei Nie , Shengfeng He

Existing works in single-image human reconstruction suffer from weak generalizability due to insufficient training data or 3D inconsistencies for a lack of comprehensive multi-view knowledge. In this paper, we introduce MagicMan, a…

Computer Vision and Pattern Recognition · Computer Science 2024-08-27 Xu He , Xiaoyu Li , Di Kang , Jiangnan Ye , Chaopeng Zhang , Liyang Chen , Xiangjun Gao , Han Zhang , Zhiyong Wu , Haolin Zhuang

Novel view synthesis has observed tremendous developments since the arrival of NeRFs. However, Nerf models overfit on a single scene, lacking generalization to out of distribution objects. Recently, diffusion models have exhibited…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Rukhshanda Hussain , Hui Xian Grace Lim , Borchun Chen , Mubarak Shah , Ser Nam Lim

We consider the problem of editing 3D objects and scenes based on open-ended language instructions. A common approach to this problem is to use a 2D image generator or editor to guide the 3D editing process, obviating the need for 3D data.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Minghao Chen , Iro Laina , Andrea Vedaldi

We introduce "ImageDream," an innovative image-prompt, multi-view diffusion model for 3D object generation. ImageDream stands out for its ability to produce 3D models of higher quality compared to existing state-of-the-art,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Peng Wang , Yichun Shi

Generating multi-view human images from a single view is a complex and significant challenge. Although recent advancements in multi-view object generation have shown impressive results with diffusion models, novel view synthesis for humans…

Computer Vision and Pattern Recognition · Computer Science 2024-12-05 Yu Feng , Shunsi Zhang , Jian Shu , Hanfeng Zhao , Guoliang Pang , Chi Zhang , Hao Wang

In the rapidly evolving field of 3D reconstruction, 3D Gaussian Splatting (3DGS) and 2D Gaussian Splatting (2DGS) represent significant advancements. Although 2DGS compresses 3D Gaussian primitives into 2D Gaussian surfels to effectively…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Zhuoxiao Li , Shanliang Yao , Yijie Chu , Angel F. Garcia-Fernandez , Yong Yue , Eng Gee Lim , Xiaohui Zhu

Modern learning-based approaches to 3D-aware image synthesis achieve high photorealism and 3D-consistent viewpoint changes for the generated images. Existing approaches represent instances in a shared canonical space. However, for…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Katja Schwarz , Seung Wook Kim , Jun Gao , Sanja Fidler , Andreas Geiger , Karsten Kreis

The availability of large-scale multimodal datasets and advancements in diffusion models have significantly accelerated progress in 4D content generation. Most prior approaches rely on multiple image or video diffusion models, utilizing…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Hanwen Liang , Yuyang Yin , Dejia Xu , Hanxue Liang , Zhangyang Wang , Konstantinos N. Plataniotis , Yao Zhao , Yunchao Wei

Recent 3D large reconstruction models typically employ a two-stage process, including first generate multi-view images by a multi-view diffusion model, and then utilize a feed-forward model to reconstruct images to 3D content.However,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Zhenyu Tang , Junwu Zhang , Xinhua Cheng , Wangbo Yu , Chaoran Feng , Yatian Pang , Bin Lin , Li Yuan

Most text-to-3D generators build upon off-the-shelf text-to-image models trained on billions of images. They use variants of Score Distillation Sampling (SDS), which is slow, somewhat unstable, and prone to artifacts. A mitigation is to…

Computer Vision and Pattern Recognition · Computer Science 2024-02-14 Luke Melas-Kyriazi , Iro Laina , Christian Rupprecht , Natalia Neverova , Andrea Vedaldi , Oran Gafni , Filippos Kokkinos

Faithfully reconstructing textured meshes is crucial for many applications. Compared to text or image modalities, leveraging 3D colored point clouds as input (colored-PC-to-mesh) offers inherent advantages in comprehensively and precisely…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Qiao Yu , Xianzhi Li , Yuan Tang , Xu Han , Jinfeng Xu , Long Hu , Min Chen

Score Distillation Sampling (SDS) has emerged as a prevalent technique for text-to-3D generation, enabling 3D content creation by distilling view-dependent information from text-to-2D guidance. However, they frequently exhibit shortcomings…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Zeyu Cai , Duotun Wang , Yixun Liang , Zhijing Shao , Ying-Cong Chen , Xiaohang Zhan , Zeyu Wang

Recently, 3D Gaussian Splatting (3DGS) has enabled photorealistic view synthesis at high inference speeds. However, its splatting-based rendering model makes several approximations to the rendering equation, reducing physical accuracy. We…

Computer Vision and Pattern Recognition · Computer Science 2025-05-22 Chinmay Talegaonkar , Yash Belhe , Ravi Ramamoorthi , Nicholas Antipa

We introduce GeoGS3D, a novel two-stage framework for reconstructing detailed 3D objects from single-view images. Inspired by the success of pre-trained 2D diffusion models, our method incorporates an orthogonal plane decomposition…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Qijun Feng , Zhen Xing , Zuxuan Wu , Yu-Gang Jiang