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While image diffusion models have made significant progress in text-driven 3D content creation, they often fail to accurately capture the intended meaning of text prompts, especially for view information. This limitation leads to the Janus…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 Zhipeng Hu , Minda Zhao , Chaoyi Zhao , Xinyue Liang , Lincheng Li , Zeng Zhao , Changjie Fan , Xiaowei Zhou , Xin Yu

We present DreamCraft3D, a hierarchical 3D content generation method that produces high-fidelity and coherent 3D objects. We tackle the problem by leveraging a 2D reference image to guide the stages of geometry sculpting and texture…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Jingxiang Sun , Bo Zhang , Ruizhi Shao , Lizhen Wang , Wen Liu , Zhenda Xie , Yebin Liu

Text-to-3D with diffusion models has achieved remarkable progress in recent years. However, existing methods either rely on score distillation-based optimization which suffer from slow inference, low diversity and Janus problems, or are…

Computer Vision and Pattern Recognition · Computer Science 2023-11-27 Jiahao Li , Hao Tan , Kai Zhang , Zexiang Xu , Fujun Luan , Yinghao Xu , Yicong Hong , Kalyan Sunkavalli , Greg Shakhnarovich , Sai Bi

Reconstructing 3D scenes and synthesizing novel views from sparse input views is a highly challenging task. Recent advances in video diffusion models have demonstrated strong temporal reasoning capabilities, making them a promising tool for…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Yuqi Zhang , Guanying Chen , Jiaxing Chen , Chuanyu Fu , Chuan Huang , Shuguang Cui

With the increasing popularity of autonomous driving based on the powerful and unified bird's-eye-view (BEV) representation, a demand for high-quality and large-scale multi-view video data with accurate annotation is urgently required.…

Computer Vision and Pattern Recognition · Computer Science 2023-10-13 Xiaofan Li , Yifu Zhang , Xiaoqing Ye

Recent advances in text-to-image generation with diffusion models present transformative capabilities in image quality. However, user controllability of the generated image, and fast adaptation to new tasks still remains an open challenge,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Omer Bar-Tal , Lior Yariv , Yaron Lipman , Tali Dekel

Benefiting from the rapid development of 2D diffusion models, 3D content generation has witnessed significant progress. One promising solution is to finetune the pre-trained 2D diffusion models to produce multi-view images and then…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Fan Yang , Jianfeng Zhang , Yichun Shi , Bowen Chen , Chenxu Zhang , Huichao Zhang , Xiaofeng Yang , Xiu Li , Jiashi Feng , Guosheng Lin

Recent advances in sparse voxel representations have significantly improved the quality of 3D content generation, enabling high-resolution modeling with fine-grained geometry. However, existing frameworks suffer from severe computational…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Yiwen Chen , Zhihao Li , Yikai Wang , Hu Zhang , Qin Li , Chi Zhang , Guosheng Lin

Event cameras or dynamic vision sensors (DVS) record asynchronous response to brightness changes instead of conventional intensity frames, and feature ultra-high sensitivity at low bandwidth. The new mechanism demonstrates great advantages…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Bo Zhang , Yuqi Han , Jinli Suo , Qionghai Dai

Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Existing 3D drag-based editing methods, whether employing…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Honghua Chen , Yushi Lan , Yongwei Chen , Yifan Zhou , Xingang Pan

3D object reconstruction from single-view image is a fundamental task in computer vision with wide-ranging applications. Recent advancements in Large Reconstruction Models (LRMs) have shown great promise in leveraging multi-view images…

Computer Vision and Pattern Recognition · Computer Science 2025-03-13 Zhiyuan Wu , Xibin Song , Senbo Wang , Weizhe Liu , Jiayu Yang , Ziang Cheng , Shenzhou Chen , Taizhang Shang , Weixuan Sun , Shan Luo , Pan Ji

Recent advances in diffusion models have significantly improved 3D generation, enabling the use of assets generated from an image for embodied AI simulations. However, the one-to-many nature of the image-to-3D problem limits their use due…

Computer Vision and Pattern Recognition · Computer Science 2025-02-26 Onat Şahin , Mohammad Altillawi , George Eskandar , Carlos Carbone , Ziyuan Liu

Recently, the emergence of diffusion models has opened up new opportunities for single-view reconstruction. However, all the existing methods represent the target object as a closed mesh devoid of any structural information, thus neglecting…

Graphics · Computer Science 2024-05-28 Anran Liu , Cheng Lin , Yuan Liu , Xiaoxiao Long , Zhiyang Dou , Hao-Xiang Guo , Ping Luo , Wenping Wang

We study the problem of single-image 3D object reconstruction. Recent works have diverged into two directions: regression-based modeling and generative modeling. Regression methods efficiently infer visible surfaces, but struggle with…

Computer Vision and Pattern Recognition · Computer Science 2025-01-09 Zixuan Huang , Mark Boss , Aaryaman Vasishta , James M. Rehg , Varun Jampani

Diffusion-based video editing have reached impressive quality and can transform either the global style, local structure, and attributes of given video inputs, following textual edit prompts. However, such solutions typically incur heavy…

Computer Vision and Pattern Recognition · Computer Science 2024-09-02 Kumara Kahatapitiya , Adil Karjauv , Davide Abati , Fatih Porikli , Yuki M. Asano , Amirhossein Habibian

Using image as prompts for 3D generation demonstrate particularly strong performances compared to using text prompts alone, for images provide a more intuitive guidance for the 3D generation process. In this work, we delve into the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Seungwook Kim , Yichun Shi , Kejie Li , Minsu Cho , Peng Wang

Diffusion models in image Super-Resolution (SR) treat all image regions uniformly, which risks compromising the overall image quality by potentially introducing artifacts during denoising of less-complex regions. To address this, we propose…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Brian B. Moser , Stanislav Frolov , Federico Raue , Sebastian Palacio , Andreas Dengel

We present an inference-time diffusion sampling method to perform multi-view consistent image editing using pre-trained 2D image editing models. These models can independently produce high-quality edits for each image in a set of multi-view…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Hadi Alzayer , Yunzhi Zhang , Chen Geng , Jia-Bin Huang , Jiajun Wu

Text-to-Image generation has seen significant advancements in output realism with the advent of diffusion models. However, diffusion models encounter difficulties when tasked with generating multiple objects, frequently resulting in…

Computer Vision and Pattern Recognition · Computer Science 2026-04-23 Federico Betti , Lorenzo Baraldi , Lorenzo Baraldi , Rita Cucchiara , Nicu Sebe

We present iFusion, a novel 3D object reconstruction framework that requires only two views with unknown camera poses. While single-view reconstruction yields visually appealing results, it can deviate significantly from the actual object,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Chin-Hsuan Wu , Yen-Chun Chen , Bolivar Solarte , Lu Yuan , Min Sun
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