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Related papers: Text-to-3D Generation with Bidirectional Diffusion…

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We present 3DiffTection, a state-of-the-art method for 3D object detection from single images, leveraging features from a 3D-aware diffusion model. Annotating large-scale image data for 3D detection is resource-intensive and time-consuming.…

Computer Vision and Pattern Recognition · Computer Science 2023-11-09 Chenfeng Xu , Huan Ling , Sanja Fidler , Or Litany

3D generation methods have shown visually compelling results powered by diffusion image priors. However, they often fail to produce realistic geometric details, resulting in overly smooth surfaces or geometric details inaccurately baked in…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Ruihan Gao , Kangle Deng , Gengshan Yang , Wenzhen Yuan , Jun-Yan Zhu

With the rising industrial attention to 3D virtual modeling technology, generating novel 3D content based on specified conditions (e.g. text) has become a hot issue. In this paper, we propose a new generative 3D modeling framework called…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Muheng Li , Yueqi Duan , Jie Zhou , Jiwen Lu

This paper presents a novel method for building scalable 3D generative models utilizing pre-trained video diffusion models. The primary obstacle in developing foundation 3D generative models is the limited availability of 3D data. Unlike…

Computer Vision and Pattern Recognition · Computer Science 2024-07-22 Junlin Han , Filippos Kokkinos , Philip Torr

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

Garment sewing patterns are fundamental design elements that bridge the gap between design concepts and practical manufacturing. The generative modeling of sewing patterns is crucial for creating diversified garments. However, existing…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Xinyu Li , Qi Yao , Yuanda Wang

Current text-to-image (T2I) generation models struggle to align spatial composition with the input text, especially in complex scenes. Even layout-based approaches yield suboptimal spatial control, as their generation process is decoupled…

Computer Vision and Pattern Recognition · Computer Science 2025-07-08 Zheyuan Liu , Munan Ning , Qihui Zhang , Shuo Yang , Zhongrui Wang , Yiwei Yang , Xianzhe Xu , Yibing Song , Weihua Chen , Fan Wang , Li Yuan

Neural Radiance Fields and 3D Gaussian Splatting have revolutionized 3D reconstruction and novel-view synthesis task. However, achieving photorealistic rendering from extreme novel viewpoints remains challenging, as artifacts persist across…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Jay Zhangjie Wu , Yuxuan Zhang , Haithem Turki , Xuanchi Ren , Jun Gao , Mike Zheng Shou , Sanja Fidler , Zan Gojcic , Huan Ling

Style-guided texture generation aims to generate a texture that is harmonious with both the style of the reference image and the geometry of the input mesh, given a reference style image and a 3D mesh with its text description. Although…

Computer Vision and Pattern Recognition · Computer Science 2024-11-04 Zhiyu Xie , Yuqing Zhang , Xiangjun Tang , Yiqian Wu , Dehan Chen , Gongsheng Li , Xaogang Jin

3D building generation with low data acquisition costs, such as single image-to-3D, becomes increasingly important. However, most of the existing single image-to-3D building creation works are restricted to those images with specific…

Computer Vision and Pattern Recognition · Computer Science 2023-09-04 Yao Wei , George Vosselman , Michael Ying Yang

While 3D generative models have greatly improved artists' workflows, the existing diffusion models for 3D generation suffer from slow generation and poor generalization. To address this issue, we propose a two-stage approach named Hunyuan3D…

Recent progress in text-to-3D object generation enables the synthesis of detailed geometry from text input by leveraging 2D diffusion models and differentiable 3D representations. However, the approaches often suffer from limited…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Ming He , Zhixiang Chen , Steve Maddock

The remarkable progress in 3D face reconstruction has resulted in high-detail and photorealistic facial representations. Recently, Diffusion Models have revolutionized the capabilities of generative methods by surpassing the performance of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Stathis Galanakis , Alexandros Lattas , Stylianos Moschoglou , Stefanos Zafeiriou

Text-to-Image (T2I) generation methods based on diffusion model have garnered significant attention in the last few years. Although these image synthesis methods produce visually appealing results, they frequently exhibit spelling errors…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Yiming Zhao , Zhouhui Lian

The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for creating imaginative 3D assets across various real-world scenarios. While recent advancements in text-to-3D…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Yixun Liang , Xin Yang , Jiantao Lin , Haodong Li , Xiaogang Xu , Yingcong Chen

In the realm of text-to-3D generation, utilizing 2D diffusion models through score distillation sampling (SDS) frequently leads to issues such as blurred appearances and multi-faced geometry, primarily due to the intrinsically noisy nature…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Pengsheng Guo , Hans Hao , Adam Caccavale , Zhongzheng Ren , Edward Zhang , Qi Shan , Aditya Sankar , Alexander G. Schwing , Alex Colburn , Fangchang Ma

Recent advances in generative modeling -- particularly diffusion models and flow matching -- have achieved remarkable success in synthesizing discrete data such as images and videos. However, adapting these models to physical applications…

Machine Learning · Computer Science 2025-11-26 Sifan Wang , Zehao Dou , Siming Shan , Tong-Rui Liu , Lu Lu

We introduce RealmDreamer, a technique for generating forward-facing 3D scenes from text descriptions. Our method optimizes a 3D Gaussian Splatting representation to match complex text prompts using pretrained diffusion models. Our key…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Jaidev Shriram , Alex Trevithick , Lingjie Liu , Ravi Ramamoorthi

Recent one image to 3D generation methods commonly adopt Score Distillation Sampling (SDS). Despite the impressive results, there are multiple deficiencies including multi-view inconsistency, over-saturated and over-smoothed textures, as…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Junwu Zhang , Zhenyu Tang , Yatian Pang , Xinhua Cheng , Peng Jin , Yida Wei , Munan Ning , Li Yuan

Current video diffusion models achieve impressive generation quality but struggle in interactive applications due to bidirectional attention dependencies. The generation of a single frame requires the model to process the entire sequence,…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Tianwei Yin , Qiang Zhang , Richard Zhang , William T. Freeman , Fredo Durand , Eli Shechtman , Xun Huang